Kernel binary regression with multiple covariates

Hidenori Okumura

In this paper, we consider kernel-based estimators in the nonparametric binary regression problem with multidimensional covariates. We propose a local linear type estimator of the response probability function with kernel weighted at each observed covariate. In addition, we discuss the rule of thumb bandwidth selector and the plug-in bandwidth selector. The efficiency of the weighted local linear estimator is determined from results of asymptotic properties and our simulation study.

Journal of the Japan Statistical Society

THE JAPAN STATISTICAL SOCIETY

41

1

1

16

10.14490/jjss.41.001

https://doi.org/10.14490/jjss.41.001
http://ci.nii.ac.jp/naid/130002112995
https://jlc.jst.go.jp/DN/JALC/00389080983?from=CiNii