seminars:stat:170406
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| seminars:stat:170406 [2017/03/22 19:30] – sdang | seminars:stat:170406 [2017/04/03 17:26] (current) – sdang | ||
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| + | ^ **TITLE:**| Model-Free Variable Selection with Matrix-Valued Predictors| | ||
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| + | We introduce a novel framework for model-free variable selection with matrix-valued predictors. To test the importance of rows, columns, and submatrices of the predictor matrix in terms of predicting the response, three types of hypotheses are formulated under a unified framework. An asymptotic test as well as a simple permutation test procedure are used to approximate the null distribution of the test statistics for all three tests. A nonparametric maximum ratio criteria (MRC) is proposed for the purpose of model-free variable selection. | ||
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