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Density estimation in line transect sampling with grouped data by local least squares
Author(s) -
Barabesi Lucio,
Greco Luigi,
Naddeo Stefania
Publication year - 2002
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.524
Subject(s) - estimator , statistics , mathematics , monte carlo method , kernel density estimation , sampling (signal processing) , kernel (algebra) , least squares function approximation , econometrics , computer science , filter (signal processing) , combinatorics , computer vision
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 new method presents interesting theoretical properties and it produces accurate and robust estimators, as is shown in a Monte Carlo study. Copyright © 2002 John Wiley & Sons, Ltd.