CONDITIONAL PROBABILITY DENSITY AND REGRESSION FUNCTION ESTIMATIONS WITH TRANSFORMATION OF DATA - Collections

＜journal article＞
CONDITIONAL PROBABILITY DENSITY AND REGRESSION FUNCTION ESTIMATIONS WITH TRANSFORMATION OF DATA

Creator	Author PID 30823190 Creator Name Moriyama, Taku 森山, 卓モリヤマ, タク Affiliation Affiliation Name Dept. of Management of Social Systems and Civil Eng., Tottori University 鳥取大学
Creator	Author PID 30173701 Creator Name Maesono, Yoshihiko 前園, 宜彦マエソノ, ヨシヒコ Affiliation Affiliation Name Department of Mathematics, Chuo University 中央大学
Language	English
Publisher	Research Association of Statistical Sciences
Publisher	統計科学研究会
Date	2020
Source Title	Bulletin of informatics and cybernetics
Vol	52
Issue	1
First Page	1
Last Page	25
Publication Type	Version of Record
Access Rights	open access
Crossref DOI	https://doi.org/10.5109/2558879
Abstract	This study extends ‘empirical transformation’ in kernel smoothing to conditional probability density and regression function estimations. We propose nonparametric conditional probability density and r...egression function estimators, which are based on an extension of ´Cwik and Mielniczuk (1989)’s method. We derived asymptotic properties of the proposed estimators and conducted a simulation that showed mean squared errors of conditional probability density and regression function estimators.show more

File	FileType	Size	Views	Description
BIC-52-1	pdf	174 KB	614

PISSN	0286-522X
EISSN	2435-743X
NCID	AA10634475
Record ID	2558879
Peer-Reviewed	Refereed
Subject Terms	conditional probability density
	mean squared error
	nonparametric estimation
	regression function
Created Date	2020.03.12
Modified Date	2023.11.20