Name
Abstract | ||
|---|---|---|
This article proposes methods for fitting piecewise loglinear models to count data with an extra-Poisson variation. Both SUPPORT (Statistica Sinica, 4 (1994) 143) and GUIDE (Statistica Sinica, 12 (2002) 361) are used for splitting methods. We developed a new bootstrap resampling method performed at each node of the tree to determine the proper size of a tree. The quasi-likelihood approach is used for fitting an extra-Poisson model at each stratum to take into account the extra variability. An adjusted Anscombe residual for the extra-Poisson model is used in this procedure. Performance of the proposed method is evaluated by a Monte Carlo simulation study. The proposed method is used to investigate geographic variability in mortality rates on lung cancer as well as effects of various demographic variability. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1016/j.csda.2004.06.011 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
monte carlo simulation study,extra-poisson variation,extra variability,quasi-likelihood,fitting piecewise loglinear model,splitting method,generalized linear model,statistica sinica,regression tree,various demographic variability,geographic variability,count data,carcinogenicity,recursive partitioning,extra poisson variation,extra-poisson model,quasi likelihood,poisson model,general linear model,monte carlo simulation,mortality rate | Econometrics,Quasi-likelihood,Regression analysis,Algorithm,Bootstrapping (statistics),Generalized linear model,Count data,Log-linear model,Poisson distribution,Statistics,Bootstrapping (electronics),Mathematics | Journal |
Volume | Issue | ISSN |
49 | 3 | Computational Statistics and Data Analysis |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yun-Hee Choi | 1 | 9 | 2.58 |
| Hongshik Ahn | 2 | 73 | 4.45 |
| James J Chen | 3 | 430 | 31.26 |