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• W2018674947 abstract "Varying coefficient models are a useful statistical tool to explore dynamic patterns of a regression relationship, in which the variation features of the regression coefficients are taken as the main evidence to reflect the dynamic relationship between the response and the explanatory variables. In this study, we propose a SiZer approach as a visually diagnostic device to uncover the statistically significant features of the coefficients. This method can highlight the significant structures of the coefficients under different scales and can therefore extract relatively full information in the data. The simulation studies and real-world data analysis show that the SiZer approach performs satisfactorily in mining the significant features of the coefficients." @default.
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• W2018674947 date "2012-11-01" @default.
• W2018674947 modified "2023-09-24" @default.
• W2018674947 title "SiZer Inference for Varying Coefficient Models" @default.
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• W2018674947 doi "https://doi.org/10.1080/03610918.2011.627102" @default.
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