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- W1992077275 abstract "To determine whether each coefficient is equal to zero or not, usual <TEX>$t$</TEX>-tests are a popular choice (among others) in linear regression to practitioners because all statistical packages provide the statistics and their corresponding <TEX>$p$</TEX>-values. Under smaller samples (especially with non-normal errors) the tests often fail to correctly detect statistical significance. We propose a permutation approach by adopting a sufficient dimension reduction methodology to overcome this deficit. Numerical studies confirm that the proposed method has potential advantages over the t-tests. In addition, data analysis is also presented." @default.
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- W1992077275 date "2013-03-31" @default.
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- W1992077275 title "Permutation Predictor Tests in Linear Regression" @default.
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- W1992077275 doi "https://doi.org/10.5351/csam.2013.20.2.147" @default.
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