Regression Optimality of Principal Components
نویسندگان
چکیده
منابع مشابه
Nonparametric Principal Components Regression
In ordinary least squares regression, dimensionality is a sensitive issue. As the number of independent variables approaches the sample size, the least squares algorithm could easily fail, i.e., estimates are not unique or very unstable, (Draper and Smith, 1981). There are several problems usually encountered in modeling high dimensional data, including the difficulty of visualizing the data, s...
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Multiple regression with correlated predictor variables is relevant to a broad range of problems in the physical, chemical, and engineering sciences. Chemometricians, in particular, have made heavy use of principal components regression and related procedures for predicting a response variable from a large number of highly correlated predictors. In this paper we develop a general theory that gu...
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ژورنال
عنوان ژورنال: The Annals of Mathematical Statistics
سال: 1972
ISSN: 0003-4851
DOI: 10.1214/aoms/1177692482