Generalized linear–quadratic model with a change point due to a covariate threshold

Feipeng Zhang, Jiejing Yang, Lei Liu, Yuan Yu

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

In this article, we develop a generalized linear–quadratic model with a change point due to a covariate threshold, with one line segment and another quadratic segment intersecting at a change point. A two-step method is proposed to estimate the regression coefficients and the change point. The asymptotic properties of the proposed estimator are derived by modern empirical processes theory. A sup-likelihood ratio test statistic along with its limiting distribution is used to test the existence of the change point. Simulation studies demonstrate that the proposed estimator has good finite-sample performance for different link functions. The applications of the proposed method on Down Syndrome data and Heart failure clinical records data reveal interesting insights.

Original languageEnglish
Pages (from-to)194-206
Number of pages13
JournalJournal of Statistical Planning and Inference
Volume216
DOIs
StatePublished - Jan 2022

Keywords

  • Change point
  • Generalized Linear-quadratic model
  • Sup likelihood ratio test

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