驱逐
发表于 2025-3-21 17:32:46
书目名称Introduction to Multivariate Calibration影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0473947<br><br> <br><br>书目名称Introduction to Multivariate Calibration影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0473947<br><br> <br><br>书目名称Introduction to Multivariate Calibration网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0473947<br><br> <br><br>书目名称Introduction to Multivariate Calibration网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0473947<br><br> <br><br>书目名称Introduction to Multivariate Calibration被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0473947<br><br> <br><br>书目名称Introduction to Multivariate Calibration被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0473947<br><br> <br><br>书目名称Introduction to Multivariate Calibration年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0473947<br><br> <br><br>书目名称Introduction to Multivariate Calibration年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0473947<br><br> <br><br>书目名称Introduction to Multivariate Calibration读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0473947<br><br> <br><br>书目名称Introduction to Multivariate Calibration读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0473947<br><br> <br><br>
Criteria
发表于 2025-3-21 21:34:06
Chemometrics and Multivariate Calibration,The relationship between univariate, multivariate, and multi-way calibrations is discussed, with emphasis in the analytical advantages which can be achieved in going from simple to more complex data structures.
高贵领导
发表于 2025-3-22 04:11:51
The Classical Least-Squares Model,The simplest first-order multivariate model, based on classical least-squares, is discussed. Important concepts are introduced, which are common to other advanced models, such as the regression coefficients and the first-order advantage. The main limitations of the classical model are detailed.
intrude
发表于 2025-3-22 07:46:04
The Inverse Least-Squares Model,The first and simplest inverse least-squares calibration model, also called multiple linear regression, is discussed in detail. Advantages and disadvantages are discussed for a model which today is still in use for some applications. Proposals are given for developing advanced calibration models.
违反
发表于 2025-3-22 08:53:49
http://reply.papertrans.cn/48/4740/473947/473947_5.png
headlong
发表于 2025-3-22 16:49:44
Principal Component Regression,A modern multivariate model incorporating all required characteristics is discussed, based on the combination of principal component analysis and inverse least-squares regression.
未成熟
发表于 2025-3-22 19:40:38
The Optimum Number of Latent Variables,The relevant issue of optimizing the number of latent variables in full-spectral inverse models is discussed, with emphasis on interpretation rather on statistical and mathematical issues.
反馈
发表于 2025-3-22 21:16:33
The Partial Least-Squares Model,The most popular first-order model based on partial least-squares is presented, and a range of applications are shown, from single and multiple analyte determinations to sample discrimination.
值得
发表于 2025-3-23 05:11:42
http://reply.papertrans.cn/48/4740/473947/473947_9.png
FAZE
发表于 2025-3-23 08:37:58
Mathematical Pre-processing,Multivariate calibration models sometimes require one to pre-process the instrumental data with mathematical techniques. Criteria are discussed for performing this relevant activity. The objective is to reduce the impact of physical phenomena or changes in the instrumental response over time.