Generalized weighted additive models based on distribution functions

Citations

WEB OF SCIENCE

5
Citations

SCOPUS

6

초록

In this paper, a new form of generalized additive models is proposed. The proposed models consist of a distribution function of the mean response and a weighted linear combination of distribution functions of covariates. This form does not make any structural problems on linking the mean response and covariates. Markov chain Monte Carlo methods are used to estimate the parameters within a Bayesian framework. (c) 2007 Elsevier B.V. All rights reserved.

키워드

Bayesian inference; Markov chain mome Carlo; beta mixtures; parametric transformation; LINK FUNCTIONS; LINEAR-MODELS; TRANSFORMATIONS; REGRESSION; FAMILY
제목
Generalized weighted additive models based on distribution functions
저자
Yeo, In-Kwon
DOI
10.1016/j.spl.2007.03.029
발행일
2007-07
유형
Article
저널명
Statistics and Probability Letters
권
77
호
12
페이지
1394 ~ 1402