Model checking for generalized partially linear models

Xinmin Li, Haozhe Liang, Wolfgang Härdle and Hua Liang ()
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Xinmin Li: Qingdao University
Haozhe Liang: University of Science and Technology of China
Wolfgang Härdle: Blockchain Research Center
Hua Liang: George Washington University

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2024, vol. 33, issue 2, No 1, 378 pages

Abstract: Abstract We propose a residual-marked empirical process test to check goodness of fit for generalized partially linear models. The proposed test can gain dimension reduction, is shown to be consistent, and can detect root-n local alternatives. We further establish asymptotic distributions of the proposed test under the null hypothesis and analyze asymptotic properties under the local and global alternatives, and suggest a bootstrap procedure for calculating the critical value. We investigate its numerical performance by simulation experiments and illustrate its utilization in two real data examples.

Keywords: Consistent test; Curse of dimensionality; Dimension reduction; Model-based bootstrap; Projection; Residual-marked empirical processes; Primary 62G10; Secondary 62J12 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11749-023-00897-4

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