A New Method for Estimation of Resource Selection Probability Function

被引：88

作者：

Lele, Subhash R. ^{[1
]}

机构：

[1] Univ Alberta, Dept Math & Stat Sci, Edmonton, AB T6G 2G1, Canada

来源：

JOURNAL OF WILDLIFE MANAGEMENT | 2009年 / 73卷 / 01期

关键词：

Bayesian estimation; data cloning; logistic regression; log-log link; maximum likelihood estimation; Monte Carlo; partial likelihood; resource selection function; use-available study design; weighted distributions; MAXIMUM-LIKELIHOOD-ESTIMATION; MODELS;

D O I：

10.2193/2007-535

中图分类号：

Q14 [生态学（生物生态学）];

学科分类号：

071012 ; 0713 ;

摘要：

Weighted distributions can be used to fit various forms of resource selection probability functions (RSPF) under the use-versus-available study design (Lele and Keim 2006). Although valid, the numerical maximization procedure used by Lele and Keim ( 2006) is unstable because of the inherent roughness of the Monte Carlo likelihood function. We used a combination of the methods of partial likelihood and data cloning to obtain maximum likelihood estimators of the RSPF in a numerically stable fashion. We demonstrated the methodology using simulated data sets generated under the log-log RSPF model and a reanalysis of telemetry data presented in Lele and Keim ( 2006) using the logistic RSPF model. The new method for estimation of RSPF can be used to understand differential selection of resources by animals, an essential component of studies in conservation biology, wildlife management, and applied ecology. ( JOURNAL OF WILDLIFE MANAGEMENT 73( 1): 122-127; 2009)

引用

页码：122 / 127

页数：6