Estimation of nonparametric ordinal logistic regression model using local maximum likelihood estimation

Marisa Rifada, Nur Chamidah, Vita Ratnasari, Purhadi

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Ordinal logistic regression is a statistical method used to analyze the ordinal response variable with three or more categories and predictor variables that are categorical or continuous. The parametric models for ordinal response variable assume that the predictor is given by a linear form of covariates. In this study, the parametric models are extended to include smooth components based on nonparametric approach. The covariates are modeled as unspecified but smooth functions. Estimation is based on local maximum likelihood estimation (LMLE).

Original languageEnglish
Article number28
JournalCommunications in Mathematical Biology and Neuroscience
Volume2021
DOIs
Publication statusPublished - 2021

Keywords

  • Local maximum likelihood estimation
  • Nonparametric
  • Ordinal logistic

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