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.

引用

页码：167 / 176

页数：10

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