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线性回归中的敏感性分析AI 解读

The Prediction Matrix Role of Variables in a Regression Equation Effects of an Observation on a Regression Equation Assessing the Influence of Multiple Observations Joint Impact of a Variable and an Observation Assessing the Effect of Errors of Measurements A Study of Model Sensitivity by the Generalized Linear Model Approach Computational Considerations. Appendix: Summary of Vector and Matrix Norms, Proofs of Three Theorems.

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回归中的残差与影响AI 解读

Conlputat ions E.ratnple 2.3.4Jer Jiyhters no.I 2.3.3Partial residual plots Esantple 2.3.5 Jef fiyhrers no. 2 2.3.4Probability plots E.ratrtpIe 2.3.6 Cloud seeditty no. 4 2.4 Transformations 2.4.1 Fanlilies of fratlsjorr~ratiot~s 2.4.2Selectb~g a trat~s/'orrtlatiott Itr~.ariattceNor~rrality Choice c?/'trtodel i ~t t c i scalirlg the predictors It~f'erettce E.uan~ple 2.4.1 Tree data 110.I 2.4.3Diagnostic ntetttods A tkinson 's method Andrew' nterhod Application to the power…

实例回归分析AI 解读

Simple Linear Regression Multiple Linear Regression Regression Diagnostics: Detection of Model Violations Qualitative Variables as Predictors Transformation of Variables Weighted Least Squares The Problem of Correlated Errors Analysis of Collinear Data Biased Estimation of Regression Coefficients Variable Selection Procedures Logistic Regression Appendix References Index.

多个总体回归的分类与估计AI 解读

Two problems, classifying an individual into one of several populations and estimating the regression in that population, are simultaneously treated as one problem. This can be viewed as a problem of a missing observation on a categorical variable. When all variables are jointly distributed multivariate normal, the maximum likelihood solution is the intuitively appealing one: classify the individual using the usual likelihood ratio procedure, then estimate the regression…

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信贷筛选的非参数方法AI 解读

Most commonly used credit screening methods are based on Fisher's linear discriminant function for quantitative variates. The variables actually used in credit scoring are usually, however, qualitative occurring as high/low, or present/ absent. We present a nonparametric approach to the credit screening problem. In our method we do not assume multivariate normality nor do we apply any arbitrary scaling procedures to the qualitative variables. We classify an observation to…

信用筛选的非参数方法AI 解读

Most commonly used credit screening methods are based on Fisher's linear discriminant function for quantitative variates. The variables actually used in credit scoring are usually, however, qualitative occurring as high/low, or present/ absent. We present a nonparametric approach to the credit screening problem. In our method we do not assume multivariate normality nor do we apply any arbitrary scaling procedures to the qualitative variables. We classify an observation to…