文章基本信息

标题：A Weighted Exponential Detection Function Model for Line Transect Data
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作者：Ababneh, Faisal ; Eidous, Omar M.
期刊名称：Journal of Modern Applied Statistical Methods
出版年度：2012
卷号：11
期号：1
页码：11
出版社：Wayne State University
摘要：A new parametric model is proposed for modeling the density function of perpendicular distances in line transects sampling. The model can be considered a weighted exponential model in the sense that it combines two exponential models with different weights. The proposed model is appealing because it is monotone decreasing with distance from transect line; in contrast to the classical exponential model, it satisfies the shoulder condition at the origin. Simulation results for a wide range of target densities show reasonable and good performances of the weighted exponential model in most considered cases compared to the classical exponential and the half-normal models.
关键词：Line transect sampling; exponential model; weighted exponential model; half-normal model