SMOOTHING SERIAL COUNT DATA THROUGH A STATE-SPACE MODEL

被引：14

作者：

KASHIWAGI, N

YANAGIMOTO, T

机构：

[1] Institute of Statistical Mathematics, Minato-ku, Tokyo 106

来源：

BIOMETRICS | 1992年 / 48卷 / 04期

关键词：

NON-GAUSSIAN SMOOTHING; POISSON DISTRIBUTION; RECURSIVE FORMULA; SURVEILLANCE DATA; TEST FOR HOMOGENEITY;

D O I：

10.2307/2532709

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

A method is proposed for smoothing serial Poisson count data through state-space modeling. Recursive formulas for evaluating the exact likelihood are given. The exact likelihood yields the likelihood ratio test for homogeneity of the Poisson means. The method is versatile enough to permit various extensions, including that for serial binomial data. The proposed method is applied to three sets of weekly disease incidence data.

引用

页码：1187 / 1194

页数：8

共 18 条

[1]

Dahlquist G., 1974, NUMERICAL METHODS

[2] STEINS ESTIMATION RULE AND ITS COMPETITORS - EMPIRICAL BAYES APPROACH [J].