Parameter Estimation and Hypothesis Testing of Geographically Weighted Multivariate Generalized Poisson Regression

被引：2
|
作者：
Berliana, Sarni Maniar [1 ,2 ]
Purhadi [1 ]
Sutikno [1 ]
Rahayu, Santi Puteri [1 ]
机构：
[1] Inst Teknol Sepuluh Nopember, Fac Sci & Data Analyt, Dept Stat, Surabaya 60111, Indonesia
[2] Politekn Stat STIS, Dept Stat, Jakarta 13330, Indonesia
来源：
MATHEMATICS | 2020年 / 8卷 / 09期
关键词：
spatial analysis; distribution theory; maximum likelihood estimation; likelihood ratio test;
D O I：
10.3390/math8091523
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
We introduce a new multivariate regression model based on the generalized Poisson distribution, which we called geographically-weighted multivariate generalized Poisson regression (GWMGPR) model, and we present a maximum likelihood step-by-step procedure to obtain parameters for it. We use the maximum likelihood ratio test to examine the significance of the regression parameters and to define their critical region.
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收藏
页数：14
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