E13.11 - Multivariate Analysis

SIGNIFICANCE AND USE
5.1 This practice outlines a universally applicable procedure to validate the performance of a quantitative or qualitative, empirically derived, multivariate calibration relative to an accepted reference method.  
5.2 This practice provides procedures for evaluating the capability of a calibration to provide reliable estimations relative to an accepted reference method.  
5.3 This practice provides purchasers of a measurement system that incorporates an empirically derived multivariate calibration with options for specifying validation requirements to ensure that the system is capable of providing estimations with an appropriate degree of agreement with an accepted reference method.  
5.4 This practice provides the user of a measurement system that incorporates an empirically derived multivariate calibration with procedures capable of providing information that may be useful for ongoing quality assurance of the performance of the measurement system.  
5.5 Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation and only for the individual measurement system on which the practice is completely applied. It is the user's responsibility to select the property levels and the compositional characteristics of the validation samples such that they are suitable to the application. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application and specific restrictions to the permitted uses of the measurement system. Users are cautioned against extrapolation of validation results beyond the material type(s) and property range(s) used to obtain these results.  
5.6 Users are cautioned that a validated empirically derived multivariate calibration is applicable only to samples that fall within the subset population represented in the validation set. The esti...
SCOPE
1.1 This practice covers requirements for the validation of empirically derived calibrations (Note 1) such as calibrations derived by Multiple Linear Regression (MLR), Principal Component Regression (PCR), Partial Least Squares (PLS), Artificial Neural Networks (ANN), or any other empirical calibration technique whereby a relationship is postulated between a set of variables measured for a given sample under test and one or more physical, chemical, quality, or membership properties applicable to that sample.
Note 1: Empirically derived calibrations are sometimes referred to as “models” or “calibrations.” In the following text, for conciseness, the term “calibration” may be used instead of the full name of the procedure.  
1.2 This practice does not cover procedures for establishing said postulated relationship.  
1.3 This practice serves as an overview of techniques used to verify the applicability of an empirically derived multivariate calibration to the measurement of a sample under test and to verify equivalence between the properties calculated from the empirically derived multivariate calibration and the results of an accepted reference method of measurement to within control limits established for the prespecified statistical confidence level.  
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.5 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
5.1 These practices can be used to establish the validity of the results obtained by an infrared (IR) spectrometer at the time the calibration is developed. The ongoing validation of estimates produced by analysis of unknown samples using the calibration model should be covered separately (see for example, Practice D6122).  
5.2 These practices are intended for all users of infrared spectroscopy. Near-infrared spectroscopy is widely used for quantitative analysis. Many of the general principles described in these practices relate to the common modern practices of near-infrared spectroscopic analysis. While sampling methods and instrumentation may differ, the general calibration methodologies are equally applicable to mid-infrared spectroscopy. New techniques are under study that may enhance those discussed within these practices. Users will find these practices to be applicable to basic aspects of the technique, to include sample selection and preparation, instrument operation, and data interpretation.  
5.3 The calibration procedures define the range over which measurements are valid and demonstrate whether or not the sensitivity and linearity of the analysis outputs are adequate for providing meaningful estimates of the specific physical or chemical characteristics of the types of materials for which the calibration is developed.
SCOPE
1.1 These practices cover a guide for the multivariate calibration of infrared spectrometers used in determining the physical or chemical characteristics of materials. These practices are applicable to analyses conducted in the near infrared (NIR) spectral region (roughly 780 to 2500 nm) through the mid infrared (MIR) spectral region (roughly 4000 to 400 cm−1).
Note 1: While the practices described herein deal specifically with mid- and near-infrared analysis, much of the mathematical and procedural detail contained herein is also applicable for multivariate quantitative analysis done using other forms of spectroscopy. The user is cautioned that typical and best practices for multivariate quantitative analysis using other forms of spectroscopy may differ from practices described herein for mid- and near-infrared spectroscopies.  
1.2 Procedures for collecting and treating data for developing IR calibrations are outlined. Definitions, terms, and calibration techniques are described. Criteria for validating the performance of the calibration model are described.  
1.3 The implementation of these practices require that the IR spectrometer has been installed in compliance with the manufacturer's specifications. In addition, it assumes that, at the times of calibration and of validation, the analyzer is operating at the conditions specified by the manufacturer.  
1.4 These practices cover techniques that are routinely applied in the near and mid infrared spectral regions for quantitative analysis. The practices outlined cover the general cases for coarse solids, fine ground solids, and liquids. All techniques covered require the use of a computer for data collection and analysis.  
1.5 These practices provide a questionnaire against which multivariate calibrations can be examined to determine if they conform to the requirements defined herein.  
1.6 For some multivariate spectroscopic analyses, interferences and matrix effects are sufficiently small that it is possible to calibrate using mixtures that contain substantially fewer chemical components than the samples that will ultimately be analyzed. While these surrogate methods generally make use of the multivariate mathematics described herein, they do not conform to procedures described herein, specifically with respect to the handling of outliers. Surrogate methods may indicate that they make use of the mathematics described herein, but they should not claim to follow the procedures described herein.  
1.7 The values stated in SI units are to be regarded as standard. No other units of measurement are...

SIGNIFICANCE AND USE
5.1 This practice should be used by the developer of standard test methods that employ surrogate calibrations.  
5.1.1 This practice assists the test method developer in setting and documenting requirements for the spectrometer/spectrophotometers that can perform the test method.  
5.1.2 This practice assists the test method developer in setting and documenting spectral data collection and computation parameters for the test method.  
5.1.3 This practice assists the test method developer in selecting among possible multivariate analysis procedures that could be used to establish the surrogate calibration. The practice describes statistical tests that should be performed to ensure that all multivariate analysis procedures that are allowed within the scope of the test method produce statistically indistinguishable results.  
5.1.4 This practice describes statistical calculations that the test method developer should perform on the calibration and qualification data that should be collected as part of the ILS that establishes the test method precision. These calculations establish the level of performance that spectrometers/spectrophotometers must meet in order to perform the test method.  
5.2 This practice describes how the person who calibrates a spectrometer/spectrophotometer can test the performance of said spectrometer/spectrophotometer to determine if the performance is adequate to conduct the test method.  
5.3 This practice describes how the user of a spectrometer/spectrophotometer can qualify the spectrometer/spectrophotometer to conduct the test method.
SCOPE
1.1 This practice relates to the multivariate calibration of spectrometers and spectrophotometers used in determining the physical and chemical characteristics of materials. A detailed description of general multivariate analysis is given in Practices E1655. This standard refers only to those instances where surrogate mixtures can be used to establish a suitable calibration matrix. This practice specifies calibration and qualification data set requirements for interlaboratory studies (ILSs), that is, round robins, of standard test methods employing surrogate calibration techniques that do not conform exactly to Practices E1655.
Note 1: For some multivariate spectroscopic analyses, interferences and matrix effects are sufficiently small that it is possible to calibrate using mixtures that contain substantially fewer chemical components than the samples that will ultimately be analyzed. While these surrogate methods generally make use of the multivariate mathematics described in Practices E1655, they do not conform to procedures described therein, specifically with respect to the handling of outliers.  
1.2 This practice specifies how the ILS data is treated to establish spectrometer/spectrophotometer performance qualification requirements to be incorporated into standard test methods.
Note 2: Spectrometer/spectrophotometer qualification procedures are intended to allow the user to determine if the performance of a specific spectrometer/spectrophotometer is adequate to conduct the analysis so as to obtain results consistent with the published test method precision.  
1.2.1 The spectroscopies used in the surrogate test methods would include but not be limited to mid- and near-infrared, ultraviolet/visible, fluorescence and Raman spectroscopies.  
1.2.2 The surrogate calibrations covered in this practice are: multilinear regression (MLR), principal components regression (PCR) or partial least squares (PLS) mathematics. These calibration procedures are described in detail in Practices E1655.  
1.3 For surrogate test methods, this practice recommends limitations that should be placed on calibration options that are allowed in the test method. Specifically, this practice recommends that the test method developer demonstrate that all calibrations that are allowed in the test method produce statistically indistinguishable r...

SIGNIFICANCE AND USE
4.1 NIR spectroscopy is a widely used technique for quantitative analysis, and it is also becoming more widely used for the identification of organic materials, that is, qualitative analysis. In general, however, the concept of qualitative analysis as used in the NIR spectral region differs from that used in the mid-IR spectral region in that NIR qualitative analysis refers to the process of automated comparison of the spectra of unknown materials to the spectra of known materials in order to identify the unknown. This approach constitutes a library search method in which each user generates his own library.  
4.2 Historically, NIR spectroscopy as practiced with classical UV-VIS-NIR instruments using methods similar to those described in Practice E1252 was not considered to be a strong technique for qualitative analysis. Although the positions and intensities of absorption bands in specific wavelength ranges were used to confirm the presence of certain functional groups, the spectra were not considered to be specific enough to allow unequivocal identification of unknown materials. A few important libraries of NIR spectra were developed for qualitative purposes, but the lack of suitable data handling facilities limited the scope of qualitative analysis severely. Furthermore, earlier work was limited almost entirely to liquid samples.  
4.3 Currently, the mid-IR procedure of deducing the structure of an unknown material by method of analysis of the locations, strengths, and positional shifts of individual absorption bands is generally not used in the NIR.  
4.4 With the development of specialized NIR instruments and mathematical algorithms for treating the data, it became possible to obtain a wealth of information from NIR spectra that had hitherto gone unused. While the mathematical algorithms described in this practice can be applied to spectral data in any region, this practice describes their application to the NIR.  
4.5 The application of NIR spectroscopy to...
SCOPE
1.1 This practice covers the use of near-infrared (NIR) spectroscopy for the qualitative analysis of liquids and solids. The practice is written under the assumption that most NIR qualitative analyses will be performed with instruments designed specifically for this region and equipped with computerized data handling algorithms. In principle, however, the practice also applies to work with liquid samples using instruments designed for operation over the ultraviolet (UV), visible, and mid-infrared (IR) regions if suitable data handling capabilities are available. Many Fourier Transform Infrared (FTIR) (normally considered mid-IR instruments) have NIR capability, or at least extended-range beamsplitters that allow operation to 1.2 μm; this practice also applies to data from these instruments.  
1.2 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.  
1.3 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
5.1 These practices can be used to establish the validity of the results obtained by an infrared (IR) spectrometer at the time the calibration is developed. The ongoing validation of estimates produced by analysis of unknown samples using the calibration model should be covered separately (see for example, Practice D6122).  
5.2 These practices are intended for all users of infrared spectroscopy. Near-infrared spectroscopy is widely used for quantitative analysis. Many of the general principles described in these practices relate to the common modern practices of near-infrared spectroscopic analysis. While sampling methods and instrumentation may differ, the general calibration methodologies are equally applicable to mid-infrared spectroscopy. New techniques are under study that may enhance those discussed within these practices. Users will find these practices to be applicable to basic aspects of the technique, to include sample selection and preparation, instrument operation, and data interpretation.  
5.3 The calibration procedures define the range over which measurements are valid and demonstrate whether or not the sensitivity and linearity of the analysis outputs are adequate for providing meaningful estimates of the specific physical or chemical characteristics of the types of materials for which the calibration is developed.
SCOPE
1.1 These practices cover a guide for the multivariate calibration of infrared spectrometers used in determining the physical or chemical characteristics of materials. These practices are applicable to analyses conducted in the near infrared (NIR) spectral region (roughly 780 to 2500 nm) through the mid infrared (MIR) spectral region (roughly 4000 to 400 cm−1).Note 1—While the practices described herein deal specifically with mid- and near-infrared analysis, much of the mathematical and procedural detail contained herein is also applicable for multivariate quantitative analysis done using other forms of spectroscopy. The user is cautioned that typical and best practices for multivariate quantitative analysis using other forms of spectroscopy may differ from practices described herein for mid- and near-infrared spectroscopies.  
1.2 Procedures for collecting and treating data for developing IR calibrations are outlined. Definitions, terms, and calibration techniques are described. Criteria for validating the performance of the calibration model are described.  
1.3 The implementation of these practices require that the IR spectrometer has been installed in compliance with the manufacturer's specifications. In addition, it assumes that, at the times of calibration and of validation, the analyzer is operating at the conditions specified by the manufacturer.  
1.4 These practices cover techniques that are routinely applied in the near and mid infrared spectral regions for quantitative analysis. The practices outlined cover the general cases for coarse solids, fine ground solids, and liquids. All techniques covered require the use of a computer for data collection and analysis.  
1.5 These practices provide a questionnaire against which multivariate calibrations can be examined to determine if they conform to the requirements defined herein.  
1.6 For some multivariate spectroscopic analyses, interferences and matrix effects are sufficiently small that it is possible to calibrate using mixtures that contain substantially fewer chemical components than the samples that will ultimately be analyzed. While these surrogate methods generally make use of the multivariate mathematics described herein, they do not conform to procedures described herein, specifically with respect to the handling of outliers. Surrogate methods may indicate that they make use of the mathematics described herein, but they should not claim to follow the procedures described herein.  
1.7 The values stated in SI units are to be regarded as standard. No other units of measurement are inc...

SIGNIFICANCE AND USE
This practice should be used by the developer of standard test methods that employ surrogate calibrations.
This practice assists the test method developer in setting and documenting requirements for the spectrometer/spectrophotometers that can perform the test method.
This practice assists the test method developer in setting and documenting spectral data collection and computation parameters for the test method.
This practice assists the test method developer in selecting among possible multivariate analysis procedures that could be used to establish the surrogate calibration. The practice describes statistical tests that should be performed to ensure that all multivariate analysis procedures that are allowed within the scope of the test method produce statistically indistinguishable results.
This practice describes statistical calculations that the test method developer should perform on the calibration and qualification data that should be collected as part of the ILS that establishes the test method precision. These calculations establish the level of performance that spectrometers/spectrophotometers must meet in order to perform the test method.
This practice describes how the person who calibrates a spectrometer/spectrophotometer can test the performance of said spectrometer/spectrophotometer to determine if the performance is adequate to conduct the test method.
This practice describes how the user of a spectrometer/spectrophotometer can qualify the spectrometer/spectrophotometer to conduct the test method.
SCOPE
1.1 This practice relates to the multivariate calibration of spectrometers and spectrophotometers used in determining the physical and chemical characteristics of materials. A detailed description of general multivariate analysis is given in Practice E1655. This standard refers only to those instances where surrogate mixtures can be used to establish a suitable calibration matrix. This practice specifies calibration and qualification data set requirements for interlaboratory studies (ILSs), that is, round robins, of standard test methods employing surrogate calibration techniques that do not conform exactly to Practices E1655.
Note 1—For some multivariate spectroscopic analyses, interferences and matrix effects are sufficiently small that it is possible to calibrate using mixtures that contain substantially fewer chemical components than the samples that will ultimately be analyzed. While these surrogate methods generally make use of the multivariate mathematics described in Practices E1655, they do not conform to procedures described therein, specifically with respect to the handling of outliers.
1.2 This practice specifies how the ILS data is treated to establish spectrometer/spectrophotometer performance qualification requirements to be incorporated into standard test methods.
Note 2—Spectrometer/spectrophotometer qualification procedures are intended to allow the user to determine if the performance of a specific spectrometer/spectrophotometer is adequate to conduct the analysis so as to obtain results consistent with the published test method precision.
1.2.1 The spectroscopies used in the surrogate test methods would include but not be limited to mid- and near-infrared, ultraviolet/visible, fluorescence and Raman spectroscopies.
1.2.2 The surrogate calibrations covered in this practice are: multilinear regression (MLR), principal components regression (PCR) or partial least squares (PLS) mathematics. These calibration procedures are described in detail in Practices E1655.
1.3 For surrogate test methods, this practice recommends limitations that should be placed on calibration options that are allowed in the test method. Specifically, this practice recommends that the test method developer demonstrate that all calibrations that are allowed in the test method produce statistically indistinguishable results.
1.4 For surrogate test methods that r...

SIGNIFICANCE AND USE
NIR spectroscopy is a widely used technique for quantitative analysis, and it is also becoming more widely used for the identification of organic materials, that is, qualitative analysis. In general, however, the concept of qualitative analysis as used in the NIR spectral region differs from that used in the mid-IR spectral region in that NIR qualitative analysis refers to the process of automated comparison of the spectra of unknown materials to the spectra of known materials in order to identify the unknown. This approach constitutes a library search method in which each user generates his own library.  
Historically, NIR spectroscopy as practiced with classical UV-VIS-NIR instruments using methods similar to those described in Practice E1252 was not considered to be a strong technique for qualitative analysis. Although the positions and intensities of absorption bands in specific wavelength ranges were used to confirm the presence of certain functional groups, the spectra were not considered to be specific enough to allow unequivocal identification of unknown materials. A few important libraries of NIR spectra were developed for qualitative purposes, but the lack of suitable data handling facilities limited the scope of qualitative analysis severely. Furthermore, earlier work was limited almost entirely to liquid samples.
Currently, the mid-IR procedure of deducing the structure of an unknown material by method of analysis of the locations, strengths, and positional shifts of individual absorption bands is generally not used in the NIR.
With the development of specialized NIR instruments and mathematical algorithms for treating the data, it became possible to obtain a wealth of information from NIR spectra that had hitherto gone unused. While the mathematical algorithms described in this practice can be applied to spectral data in any region, this practice describes their application to the NIR.  
The application of NIR spectroscopy to qualitative analysis ...
SCOPE
1.1 This practice covers the use of near-infrared (NIR) spectroscopy for the qualitative analysis of liquids and solids. The practice is written under the assumption that most NIR qualitative analyses will be performed with instruments designed specifically for this region and equipped with computerized data handling algorithms. In principle, however, the practice also applies to work with liquid samples using instruments designed for operation over the ultraviolet (UV), visible, and mid-infrared (IR) regions if suitable data handling capabilities are available. Many Fourier Transform Infrared (FTIR) (normally considered mid-IR instruments) have NIR capability, or at least extended-range beamsplitters that allow operation to 1.2 μm; this practice also applies to data from these instruments.
1.2 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.
1.3 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
This practice outlines a universally applicable procedure to validate the performance of a quantitative or qualitative, empirically derived, multivariate calibration relative to an accepted reference method.
This practice provides procedures for evaluating the capability of a calibration to provide reliable estimations relative to an accepted reference method.
This practice provides purchasers of a measurement system that incorporates an empirically derived multivariate calibration with options for specifying validation requirements to ensure that the system is capable of providing estimations with an appropriate degree of agreement with an accepted reference method.
This practice provides the user of a measurement system that incorporates an empirically derived multivariate calibration with procedures capable of providing information that may be useful for ongoing quality assurance of the performance of the measurement system.
Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation and only for the individual measurement system on which the practice is completely applied. It is the user's responsibility to select the property levels and the compositional characteristics of the validation samples such that they are suitable to the application. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application and specific restrictions to the permitted uses of the measurement system. Users are cautioned against extrapolation of validation results beyond the material type(s) and property range(s) used to obtain these results.
Users are cautioned that a validated empirically derived multivariate calibration is applicable only to samples that fall within the subset population represented in the validation set. The estimation from an empirically de...
SCOPE
1.1 This practice covers requirements for the validation of empirically derived calibrations (Note 1) such as calibrations derived by Multiple Linear Regression (MLR), Principal Component Regression (PCR), Partial Least Squares (PLS), Artificial Neural Networks (ANN), or any other empirical calibration technique whereby a relationship is postulated between a set of variables measured for a given sample under test and one or more physical, chemical, quality, or membership properties applicable to that sample.
Note 1—Empirically derived calibrations are sometimes referred to as “models” or “calibrations.” In the following text, for conciseness, the term “calibration” may be used instead of the full name of the procedure.
1.2 This practice does not cover procedures for establishing said postulated relationship.
1.3 This practice serves as an overview of techniques used to verify the applicability of an empirically derived multivariate calibration to the measurement of a sample under test and to verify equivalence between the properties calculated from the empirically derived multivariate calibration and the results of an accepted reference method of measurement to within control limits established for the prespecified statistical confidence level.
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
This practice outlines a universally applicable procedure to validate the performance of a quantitative or qualitative, empirically derived, multivariate calibration relative to an accepted reference method.
This practice provides procedures for evaluating the capability of a calibration to provide reliable estimations relative to an accepted reference method.
This practice provides purchasers of a measurement system that incorporates an empirically derived multivariate calibration with options for specifying validation requirements to ensure that the system is capable of providing estimations with an appropriate degree of agreement with an accepted reference method.
This practice provides the user of a measurement system that incorporates an empirically derived multivariate calibration with procedures capable of providing information that may be useful for ongoing quality assurance of the performance of the measurement system.
Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation and only for the individual measurement system on which the practice is completely applied. It is the user's responsibility to select the property levels and the compositional characteristics of the validation samples such that they are suitable to the application. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application and specific restrictions to the permitted uses of the measurement system. Users are cautioned against extrapolation of validation results beyond the material type(s) and property range(s) used to obtain these results.
Users are cautioned that a validated empirically derived multivariate calibration is applicable only to samples that fall within the subset population represented in the validation set. The estimation from an empirically de...
SCOPE
1.1 This practice covers requirements for the validation of empirically derived calibrations (Note 1) such as calibrations derived by Multiple Linear Regression (MLR), Principal Component Regression (PCR), Partial Least Squares (PLS), Artificial Neural Networks (ANN), or any other empirical calibration technique whereby a relationship is postulated between a set of variables measured for a given sample under test and one or more physical, chemical, quality, or membership properties applicable to that sample.
Note 1—Empirically derived calibrations are sometimes referred to as “models” or “calibrations.” In the following text, for conciseness, the term “calibration” may be used instead of the full name of the procedure.
1.2 This practice does not cover procedures for establishing said postulated relationship.
1.3 This practice serves as an overview of techniques used to verify the applicability of an empirically derived multivariate calibration to the measurement of a sample under test and to verify equivalence between the properties calculated from the empirically derived multivariate calibration and the results of an accepted reference method of measurement to within control limits established for the prespecified statistical confidence level.
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
This practice outlines a universally applicable procedure to validate the performance of a quantitative or qualitative, empirically derived, multivariate calibration relative to an accepted reference method.
This practice provides procedures for evaluating the capability of a calibration to provide reliable estimations relative to an accepted reference method.
This practice provides purchasers of a measurement system that incorporates an empirically derived multivariate calibration with options for specifying validation requirements to ensure that the system is capable of providing estimations with an appropriate degree of agreement with an accepted reference method.
This practice provides the user of a measurement system that incorporates an empirically derived multivariate calibration with procedures capable of providing information that may be useful for ongoing quality assurance of the performance of the measurement system.
Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation and only for the individual measurement system on which the practice is completely applied. It is the user's responsibility to select the property levels and the compositional characteristics of the validation samples such that they are suitable to the application. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application and specific restrictions to the permitted uses of the measurement system. Users are cautioned against extrapolation of validation results beyond the material type(s) and property range(s) used to obtain these results.
Users are cautioned that a validated empirically derived multivariate calibration is applicable only to samples that fall within the subset population represented in the validation set. The estimation from an empirically de...
SCOPE
1.1 This practice covers requirements for the validation of empirically derived calibrations (Note 1) such as calibrations derived by Multiple Linear Regression (MLR), Principal Component Regression (PCR), Partial Least Squares (PLS), Artificial Neural Networks (ANN), or any other empirical calibration technique whereby a relationship is postulated between a set of variables measured for a given sample under test and one or more physical, chemical, quality, or membership properties applicable to that sample.
Note 1—Empirically derived calibrations are sometimes referred to as “models” or “calibrations.” In the following text, for conciseness, the term “calibration” may be used instead of the full name of the procedure.
1.2 This practice does not cover procedures for establishing said postulated relationship.
1.3 This practice serves as an overview of techniques used to verify the applicability of an empirically derived multivariate calibration to the measurement of a sample under test and to verify equivalence between the properties calculated from the empirically derived multivariate calibration and the results of an accepted reference method of measurement to within control limits established for the prespecified statistical confidence level.
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
This practice outlines a universally applicable procedure to validate the performance of a quantitative or qualitative, empirically derived, multivariate calibration relative to an accepted reference method.
This practice provides procedures for evaluating the capability of a calibration to provide reliable estimations relative to an accepted reference method.
This practice provides purchasers of a measurement system that incorporates an empirically derived multivariate calibration with options for specifying validation requirements to ensure that the system is capable of providing estimations with an appropriate degree of agreement with an accepted reference method.
This practice provides the user of a measurement system that incorporates an empirically derived multivariate calibration with procedures capable of providing information that may be useful for ongoing quality assurance of the performance of the measurement system.
Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation and only for the individual measurement system on which the practice is completely applied. It is the user's responsibility to select the property levels and the compositional characteristics of the validation samples such that they are suitable to the application. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application and specific restrictions to the permitted uses of the measurement system. Users are cautioned against extrapolation of validation results beyond the material type(s) and property range(s) used to obtain these results.
Users are cautioned that a validated empirically derived multivariate calibration is applicable only to samples that fall within the subset population represented in the validation set. The estimation from an empirically de...
SCOPE
1.1 This practice covers requirements for the validation of empirically derived calibrations (Note 1) such as calibrations derived by Multiple Linear Regression (MLR), Principal Component Regression (PCR), Partial Least Squares (PLS), Artificial Neural Networks (ANN), or any other empirical calibration technique whereby a relationship is postulated between a set of variables measured for a given sample under test and one or more physical, chemical, quality, or membership properties applicable to that sample.
Note 1—Empirically derived calibrations are sometimes referred to as “models” or “calibrations.” In the following text, for conciseness, the term “calibration” may be used instead of the full name of the procedure.
1.2 This practice does not cover procedures for establishing said postulated relationship.
1.3 This practice serves as an overview of techniques used to verify the applicability of an empirically derived multivariate calibration to the measurement of a sample under test and to verify equivalence between the properties calculated from the empirically derived multivariate calibration and the results of an accepted reference method of measurement to within control limits established for the prespecified statistical confidence level.
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
This practice outlines a universally applicable procedure to validate the performance of a quantitative or qualitative, empirically derived, multivariate calibration relative to an accepted reference method.
This practice provides procedures for evaluating the capability of a calibration to provide reliable estimations relative to an accepted reference method.
This practice provides purchasers of a measurement system that incorporates an empirically derived multivariate calibration with options for specifying validation requirements to ensure that the system is capable of providing estimations with an appropriate degree of agreement with an accepted reference method.
This practice provides the user of a measurement system that incorporates an empirically derived multivariate calibration with procedures capable of providing information that may be useful for ongoing quality assurance of the performance of the measurement system.
Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation and only for the individual measurement system on which the practice is completely applied. It is the user's responsibility to select the property levels and the compositional characteristics of the validation samples such that they are suitable to the application. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application and specific restrictions to the permitted uses of the measurement system. Users are cautioned against extrapolation of validation results beyond the material type(s) and property range(s) used to obtain these results.
Users are cautioned that a validated empirically derived multivariate calibration is applicable only to samples that fall within the subset population represented in the validation set. The estimation from an empirically de...
SCOPE
1.1 This practice covers requirements for the validation of empirically derived calibrations (Note 1) such as calibrations derived by Multiple Linear Regression (MLR), Principal Component Regression (PCR), Partial Least Squares (PLS), Artificial Neural Networks (ANN), or any other empirical calibration technique whereby a relationship is postulated between a set of variables measured for a given sample under test and one or more physical, chemical, quality, or membership properties applicable to that sample.
Note 1—Empirically derived calibrations are sometimes referred to as “models” or “calibrations.” In the following text, for conciseness, the term “calibration” may be used instead of the full name of the procedure.
1.2 This practice does not cover procedures for establishing said postulated relationship.
1.3 This practice serves as an overview of techniques used to verify the applicability of an empirically derived multivariate calibration to the measurement of a sample under test and to verify equivalence between the properties calculated from the empirically derived multivariate calibration and the results of an accepted reference method of measurement to within control limits established for the prespecified statistical confidence level.
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
This practice outlines a universally applicable procedure to validate the performance of a quantitative or qualitative, empirically derived, multivariate calibration relative to an accepted reference method.
This practice provides procedures for evaluating the capability of a calibration to provide reliable estimations relative to an accepted reference method.
This practice provides purchasers of a measurement system that incorporates an empirically derived multivariate calibration with options for specifying validation requirements to ensure that the system is capable of providing estimations with an appropriate degree of agreement with an accepted reference method.
This practice provides the user of a measurement system that incorporates an empirically derived multivariate calibration with procedures capable of providing information that may be useful for ongoing quality assurance of the performance of the measurement system.
Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation and only for the individual measurement system on which the practice is completely applied. It is the user's responsibility to select the property levels and the compositional characteristics of the validation samples such that they are suitable to the application. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application and specific restrictions to the permitted uses of the measurement system. Users are cautioned against extrapolation of validation results beyond the material type(s) and property range(s) used to obtain these results.
Users are cautioned that a validated empirically derived multivariate calibration is applicable only to samples that fall within the subset population represented in the validation set. The estimation from an empirically de...
SCOPE
1.1 This practice covers requirements for the validation of empirically derived calibrations (Note 1) such as calibrations derived by Multiple Linear Regression (MLR), Principal Component Regression (PCR), Partial Least Squares (PLS), Artificial Neural Networks (ANN), or any other empirical calibration technique whereby a relationship is postulated between a set of variables measured for a given sample under test and one or more physical, chemical, quality, or membership properties applicable to that sample.
Note 1—Empirically derived calibrations are sometimes referred to as “models” or “calibrations.” In the following text, for conciseness, the term “calibration” may be used instead of the full name of the procedure.
1.2 This practice does not cover procedures for establishing said postulated relationship.
1.3 This practice serves as an overview of techniques used to verify the applicability of an empirically derived multivariate calibration to the measurement of a sample under test and to verify equivalence between the properties calculated from the empirically derived multivariate calibration and the results of an accepted reference method of measurement to within control limits established for the prespecified statistical confidence level.
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
These practices can be used to establish the validity of the results obtained by an infrared (IR) spectrometer at the time the calibration is developed. The ongoing validation of estimates produced by analysis of unknown samples using the calibration model should be covered separately (see for example, Practice D 6122).
These practices are intended for all users of infrared spectroscopy. Near-infrared spectroscopy is widely used for quantitative analysis. Many of the general principles described in these practices relate to the common modern practices of near-infrared spectroscopic analysis. While sampling methods and instrumentation may differ, the general calibration methodologies are equally applicable to mid-infrared spectroscopy. New techniques are under study that may enhance those discussed within these practices. Users will find these practices to be applicable to basic aspects of the technique, to include sample selection and preparation, instrument operation, and data interpretation.
The calibration procedures define the range over which measurements are valid and demonstrate whether or not the sensitivity and linearity of the analysis outputs are adequate for providing meaningful estimates of the specific physical or chemical characteristics of the types of materials for which the calibration is developed.
SCOPE
1.1 These practices cover a guide for the multivariate calibration of infrared spectrometers used in determining the physical or chemical characteristics of materials. These practices are applicable to analyses conducted in the near infrared (NIR) spectral region (roughly 780 to 2500 nm) through the mid infrared (MIR) spectral region (roughly 4000 to 400 cm-1).
Note 1—While the practices described herein deal specifically with mid- and near-infrared analysis, much of the mathematical and procedural detail contained herein is also applicable for multivariate quantitative analysis done using other forms of spectroscopy. The user is cautioned that typical and best practices for multivariate quantitative analysis using other forms of spectroscopy may differ from practices described herein for mid- and near-infrared spectroscopies.
1.2 Procedures for collecting and treating data for developing IR calibrations are outlined. Definitions, terms, and calibration techniques are described. Criteria for validating the performance of the calibration model are described.
1.3 The implementation of these practices require that the IR spectrometer has been installed in compliance with the manufacturer's specifications. In addition, it assumes that, at the times of calibration and of validation, the analyzer is operating at the conditions specified by the manufacturer.
1.4 These practices cover techniques that are routinely applied in the near and mid infrared spectral regions for quantitative analysis. The practices outlined cover the general cases for coarse solids, fine ground solids, and liquids. All techniques covered require the use of a computer for data collection and analysis.
1.5 These practices provide a questionnaire against which multivariate calibrations can be examined to determine if they conform to the requirements defined herein.
1.6 For some multivariate spectroscopic analyses, interferences and matrix effects are sufficiently small that it is possible to calibrate using mixtures that contain substantially fewer chemical components than the samples that will ultimately be analyzed. While these surrogate methods generally make use of the multivariate mathematics described herein, they do not conform to procedures described herein, specifically with respect to the handling of outliers. Surrogate methods may indicate that they make use of the mathematics described herein, but they should not claim to follow the procedures described herein.
1.7 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsib...

SCOPE
1.1 These practices cover a guide for the multivariate calibration of infrared spectrometers used in determining the physical or chemical characteristics of materials. These practices are applicable to analyses conducted in the near infrared (NIR) spectral region (roughly 780 to 2500 nm) through the mid infrared (MIR) spectral region (roughly 4000 to 400 cm-1).
Note 1—While the practices described herein deal specifically with mid- and near-infrared analysis, much of the mathematical and procedural detail contained herein is also applicable for multivariate quantitative analysis done using other forms of spectroscopy. The user is cautioned that typical and best practices for multivariate quantitative analysis using other forms of spectroscopy may differ from practices described herein for mid- and near-infrared spectroscopies.
1.2 Procedures for collecting and treating data for developing IR calibrations are outlined. Definitions, terms, and calibration techniques are described. Criteria for validating the performance of the calibration model are described.
1.3 The implementation of these practices require that the IR spectrometer has been installed in compliance with the manufacturer's specifications. In addition, it assumes that, at the times of calibration and of validation, the analyzer is operating at the conditions specified by the manufacturer.
1.4 These practices cover techniques that are routinely applied in the near and mid infrared spectral regions for quantitative analysis. The practices outlined cover the general cases for coarse solids, fine ground solids, and liquids. All techniques covered require the use of a computer for data collection and analysis.
1.5 These practices provide a questionnaire against which multivariate calibrations can be examined to determine if they conform to the requirements defined herein.
1.6 For some multivariate spectroscopic analyses, interferences and matrix effects are sufficiently small that it is possible to calibrate using mixtures that contain substantially fewer chemical components than the samples that will ultimately be analyzed. While these surrogate methods generally make use of the multivariate mathematics described herein, they do not conform to procedures described herein, specifically with respect to the handling of outliers. Surrogate methods may indicate that they make use of the mathematics described herein, but they should not claim to follow the procedures described herein.
1.7 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SCOPE
1.1 This practice covers the use of near-infrared (NIR) spectroscopy for the qualitative analysis of liquids and solids. The practice is written under the assumption that most NIR qualitative analyses will be performed with instruments designed specifically for this region and equipped with computerized data handling algorithms. In principle, however, the practice also applies to work with liquid samples using instruments designed for operation over the ultraviolet (UV), visible, and mid-infrared (IR) regions if suitable data handling capabilities are available. Many Fourier Transform Infrared (FTIR) (normally considered mid-IR instruments) have NIR capability, or at least extended-range beamsplitters that allow operation to 1.2 [mu]m; this practice also applies to data from these instruments.  
1.2  This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
This practice should be used by the developer of standard test methods that employ surrogate calibrations.
5.1.1 This practice assists the test method developer in setting and documenting requirements for the spectrometer/spectrophotometers that can perform the test method.
5.1.2 This practice assists the test method developer in setting and documenting spectral data collection and computation parameters for the test method.
5.1.3 This practice assists the test method developer in selecting among possible multivariate analysis procedures that could be used to establish the surrogate calibration. The practice describes statistical tests that should be performed to ensure that all multivariate analysis procedures that are allowed within the scope of the test method produce statistically indistinguishable results.
5.1.4 This practice describes statistical calculations that the test method developer should perform on the calibration and qualification data that should be collected as part of the ILS that establishes the test method precision. These calculations establish the level of performance that spectrometers/spectrophotometers must meet in order to perform the test method.
This practice describes how the person who calibrates a spectrometer/spectrophotometer can test the performance of said spectrometer/spectrophotometer to determine if the performance is adequate to conduct the test method.
This practice describes how the user of a spectrometer/spectrophotometer can qualify the spectrometer/spectrophotometer to conduct the test method.
SCOPE
1.1 This practice relates to the multivariate calibration of spectrometers and spectrophotometers used in determining the physical and chemical characteristics of materials. A detailed description of general multivariate analysis is given in Practice E1655. This standard refers only to those instances where surrogate mixtures can be used to establish a suitable calibration matrix. This practice specifies calibration and qualification data set requirements for interlaboratory studies (ILSs), that is, round robins, of standard test methods employing surrogate calibration techniques that do not conform exactly to Practices E1655.
Note 1--For some multivariate spectroscopic analyses, interferences and matrix effects are sufficiently small that it is possible to calibrate using mixtures that contain substantially fewer chemical components than the samples that will ultimately be analyzed. While these surrogate methods generally make use of the multivariate mathematics described in Practices E1655, they do not conform to procedures described therein, specifically with respect to the handling of outliers.
1.2 This practice specifies how the ILS data is treated to establish spectrometer/spectrophotometer performance qualification requirements to be incorporated into standard test methods.
Note 2--Spectrometer/spectrophotometer qualification procedures are intended to allow the user to determine if the performance of a specific spectrometer/spectrophotometer is adequate to conduct the analysis so as to obtain results consistent with the published test method precision.
1.2.1 The spectroscopies used in the surrogate test methods would include but not be limited to mid- and near-infrared, ultraviolet/visible, fluorescence and Raman spectroscopies.
1.2.2 The surrogate calibrations covered in this practice are: multilinear regression (MLR), principal components regression (PCR) or partial least squares (PLS) mathematics. These calibration procedures are described in detail in Practices E1655.
1.3 For surrogate test methods, this practice recommends limitations that should be placed on calibration options that are allowed in the test method. Specifically, this practice recommends that the test method developer demonstrate that all calibrations that are allowed in the test method produce statistically indistinguishable results.
1.4 For surrogate te...

SCOPE
1.1 This practice covers the use of near-infrared (NIR) spectroscopy for the qualitative analysis of liquids and solids. The practice is written under the assumption that most NIR qualitative analyses will be performed with instruments designed specifically for this region and equipped with computerized data handling algorithms. In principle, however, the practice also applies to work with liquid samples using instruments designed for operation over the ultraviolet (UV), visible, and mid-infrared (IR) regions if suitable data handling capabilities are available. Many Fourier Transform Infrared (FTIR) (normally considered mid-IR instruments) have NIR capability, or at least extended-range beamsplitters that allow operation to 1.2 [mu]m; this practice also applies to data from these instruments.  
1.2  This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SCOPE
1.1 This practice relates to the multivariate calibration of spectrometers and spectrophotometers used in determining the physical and chemical characteristics of materials. A detailed description of general multivariate analysis is given in Practice E1655. This standard refers only to those instances where surrogate mixtures can be used to establish a suitable calibration matrix. This practice specifies calibration and qualification data set requirements for interlaboratory studies (ILSs), that is, round robins, of standard test methods employing surrogate calibration techniques that do not conform exactly to Practices E1655.
Note 1--For some multivariate spectroscopic analyses, interferences and matrix effects are sufficiently small that it is possible to calibrate using mixtures that contain substantially fewer chemical components than the samples that will ultimately be analyzed. While these surrogate methods generally make use of the multivariate mathematics described in Practices E1655, they do not conform to procedures described therein, specifically with respect to the handling of outliers.
1.2 This practice specifies how the ILS data is treated to establish spectrometer/spectrophotometer performance qualification requirements to be incorporated into standard test methods.
Note 2--Spectrometer/spectrophotometer qualification procedures are intended to allow the user to determine if the performance of a specific spectrometer/spectrophotometer is adequate to conduct the analysis so as to obtain results consistent with the published test method precision.
1.2.1 The spectroscopies used in the surrogate test methods would include but not be limited to mid- and near-infrared, ultraviolet/visible, fluorescence and Raman spectroscopies.
1.2.2 The surrogate calibrations covered in this practice are: multilinear regression (MLR), principal components regression (PCR) or partial least squares (PLS) mathematics. These calibration procedures are described in detail in Practices E1655.
1.3 For surrogate test methods, this practice recommends limitations that should be placed on calibration options that are allowed in the test method. Specifically, this practice recommends that the test method developer demonstrate that all calibrations that are allowed in the test method produce statistically indistinguishable results.
1.4 For surrogate test methods that reference spectrometer/spectrophotometer performance practices, such as Practices E275, E387, E388, E579, E925, E932, E958, E1421, E1683, E1866 or E1944, this practice recommends that instrument performance data be collected as part of the ILS to establish the relationship between spectrometer/spectrophotometer performance and test method precision.

SCOPE
1.1 These practices cover a guide for the multivariate calibration of infrared spectrometers used in determining the physical or chemical characteristics of materials. These practices are applicable to analyses conducted in the near infrared (NIR) spectral region (roughly 780 to 2500 nm) through the mid infrared (MIR) spectral region (roughly 4000 to 400 cm-1).
Note 1--While the practices described herein deal specifically with mid- and near-infrared analysis, much of the mathematical and procedural detail contained herein is also applicable for multivariate quantitative analysis done using other forms of spectroscopy. The user is cautioned that typical and best practices for multivariate quantitative analysis using other forms of spectroscopy may differ from practices described herein for mid- and near-infrared spectroscopies.
1.2 Procedures for collecting and treating data for developing IR calibrations are outlined. Definitions, terms, and calibration techniques are described. Criteria for validating the performance of the calibration model are described.
1.3 The implementation of these practices require that the IR spectrometer has been installed in compliance with the manufacturer's specifications. In addition, it assumes that, at the times of calibration and of validation, the analyzer is operating at the conditions specified by the manufacturer.
1.4 These practices cover techniques that are routinely applied in the near and mid infrared spectral regions for quantitative analysis. The practices outlined cover the general cases for coarse solids, fine ground solids, and liquids. All techniques covered require the use of a computer for data collection and analysis.
1.5 These practices provide a questionnaire against which multivariate calibrations can be examined to determine if they conform to the requirements defined herein.
1.6 For some multivariate spectroscopic analyses, interferences and matrix effects are sufficiently small that it is possible to calibrate using mixtures that contain substantially fewer chemical components than the samples that will ultimately be analyzed. While these surrogate methods generally make use of the multivariate mathematics described herein, they do not conform to procedures described herein, specifically with respect to the handling of outliers. Surrogate methods may indicate that they make use of the mathematics described herein, but they should not claim to follow the procedures described herein.
1.7 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.