淡江大學機構典藏:Item 987654321/107627
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    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/107627


    題名: Nonparametric Methods for Line Transect Surveys in the Presence of Measurement Errors
    作者: Fei-Yin Chen;Lu-Fang Chen;Wen-Han Hwang;Yih-Huei Huang
    關鍵詞: Animal Density;Line Transect;Measurement Error;Point Transect;Kernel Smoothing
    日期: 2014-06
    上傳時間: 2016-10-05 02:10:30 (UTC+8)
    摘要: 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.
    關聯: 淡江理工學刊 17(2),頁131-140
    DOI: 10.6180/jase.2014.17.2.04
    顯示於類別:[Department of Applied Mathematics and Data Science] Journal Article

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