On regression model selection for the data with correlated errors |
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Authors: | Wen Hsiang Wei |
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Institution: | (1) Department of Statistics, Tung Hai University, Taichung, Taiwan, ROC |
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Abstract: | A class of regression model selection criteria for the data with correlated errors is proposed. The proposed class of selection
criteria is an estimator of weighted prediction risk. In addition, the proposed selection criteria are the generalizations
of several commonly used criteria in statistical analysis. The theoretical and asymptotic properties for the class of criteria
are established. Further, in the medium-sample case, the results based on a simulation study are quite consistent with the
theoretical ones. The proposed criteria perform well in the simulations. Several applications are also given for a variety
of statistical models. |
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Keywords: | Generalized cross-validation Model selection Nonparametric regression Penalized likelihood Smoothing splines |
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