Functional linear regression after spline transformation

Publication year: 2011 Source: Computational Statistics & Data Analysis, Available online 1 October 2011 Guochang Wang, Nan Lin, Baoxue Zhang Functional linear regression has been widely used to model the relationship between a scalar response and functional predictors. If the original data do not satisfy the linear assumption, an intuitive solution is to perform some transformation such that transformed data will be linearly related. The problem of finding such transformations has been rather neglected in the development of functional data analysis tools.

Publication year: 2011 Source: Computational Statistics & Data Analysis, Available online 1 October 2011 Guochang Wang, Nan Lin, Baoxue Zhang Functional linear regression has been widely used to model the relationship between a scalar response and functional predictors. If the original data do not satisfy the linear assumption, an intuitive solution is to perform some transformation such that transformed data will be linearly related. The problem of finding such transformations has been rather neglected in the development of functional data analysis tools.

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Functional linear regression after spline transformation

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