Nonparametric Methods for Line Transect Surveys in the Presence of Measurement Errors

Fei-Yin Chen; Lu-Fang Chen; Wen-Han Hwang; Yih-Huei Huang

doi:10.6180/jase.2014.17.2.04

Nonparametric Methods for Line Transect Surveys in the Presence of Measurement Errors

Fei-Yin Chen¹, Lu-Fang Chen², Wen-Han Hwang³ and Yih-Huei Huang This email address is being protected from spambots. You need JavaScript enabled to view it.¹

¹Department of Mathematics, Tamkang University, Tamsui, Taiwan 251, R.O.C.
²The Teaching Center of Natural Science, Minghsin University of Science and Technology, Hsinchu, Taiwan 304, R.O.C.
³Institute of Statistics, National Chung Hsing University, Taichung, Taiwan 402, R.O.C.

Received: November 22, 2013
Accepted: May 12, 2014
Publication Date: June 1, 2014

Download Citation: ||https://doi.org/10.6180/jase.2014.17.2.04

ABSTRACT

We consider the estimation of animal density by distance sampling line transect survey when the data of sighting distances are contaminated with measurement errors. The presence of measurement errors may result in a substantial bias on the estimation of animal density. This study investigates the effects of measurement errors while applying the nonparametric kernel density estimation. With regards to the typical additive and a general multiplicative measurement error models, we accordingly develop corrections to adjust the biases caused by measurement errors. A simulation study was carried out for comparing with other parametric approaches. An extension to the distance sampling point transect surveys is addressed as well.

Keywords: Animal Density, Line Transect, Measurement Error, Point Transect, Kernel Smoothing

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