Second-order biases of the maximum likelihood estimates in von Mises regression models

被引：11

作者：

Cordeiro, GM ^{[1
]}

Vasconcellos, KLP ^{[1
]}

机构：

[1] Univ Fed Pernambuco, Recife, PE, Brazil

来源：

AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS | 1999年 / 41卷 / 02期

关键词：

bias correction; generalized linear models; iteratively reweighted least squares; maximum likelihood estimate; von Mises regression model;

D O I：

10.1111/1467-842X.00073

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

This paper discusses issues related to the improvement of maximum likelihood estimates in von Mises regression models. It obtains general matrix expressions for the second-order biases of maximum likelihood estimates of the mean parameters and concentration parameters. The formulae are simple to compute, and give the biases by means of weighted linear regressions. Simulation results are presented assessing the performance of corrected maximum likelihood estimates in these models.

引用

页码：189 / 198

页数：10

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