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.

引用

页数：14

共 25 条

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