Forward variable selection for sparse ultra-high-dimensional generalized varying coefficient models

Toshio Honda; Chien-Tong Lin

doi:10.1007/s42081-020-00090-z

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Forward variable selection for sparse ultra-high-dimensional generalized varying coefficient models

Toshio Honda Chien-Tong Lin

Year: 2020 Journal: Japanese Journal of Statistics and Data Science Vol: 4 (1)Pages: 151-179 Publisher: Springer Science+Business Media

DOI: 10.1007/s42081-020-00090-z

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Keywords:

Covariate Feature selection Consistency (knowledge bases) Mathematics Model selection Variable (mathematics) Lasso (programming language) Feature (linguistics) Spline (mechanical) Stopping rule Computer science Applied mathematics Statistics Algorithm Mathematical optimization Artificial intelligence

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Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Statistical Methods and Bayesian Inference

Physical Sciences → Mathematics → Statistics and Probability

Bayesian Methods and Mixture Models

Physical Sciences → Computer Science → Artificial Intelligence

Forward variable selection for sparse ultra-high-dimensional generalized varying coefficient models

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