Density estimation in line transect sampling with grouped data by local least squares

被引：2
|
作者：
Barabesi, L [1 ]
Greco, L [1 ]
Naddeo, S [1 ]
机构：
[1] Univ Siena, Dipartimento Merodi Quantitat, I-53100 Siena, Italy
来源：
ENVIRONMETRICS | 2002年 / 13卷 / 02期
关键词：
distance sampling; line transect methods; grouped data; local least squares;
D O I：
10.1002/env.524
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
A semiparametric estimator for animal density in distance sampling is proposed when grouped data are on hand. The estimation technique is based on a kernel-smoothed local least-square criterion function. suitably developed for this setting. The ne v method presents interesting theoretical properties and it produces accurate and robust estimators. as is shown in a Monte Carlo Study. Copyright (C) 2002 John Wiley Sons. Ltd.
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页码：167 / 176
页数：10
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