A weighted exponential detection function model for line transect data

Faisal Ababneh, Omar M. Eidous

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)144-151
Number of pages8
JournalJournal of Modern Applied Statistical Methods
Volume11
Issue number1
Publication statusPublished - 2012

Fingerprint

Exponential Model
Line
Parametric Model
Density Function
Model
Perpendicular
Monotone
Target
Modeling
Range of data
Simulation

Keywords

  • Exponential model
  • Half-normal model
  • Line transect sampling
  • Weighted exponential model

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability

Cite this

A weighted exponential detection function model for line transect data. / Ababneh, Faisal; Eidous, Omar M.

In: Journal of Modern Applied Statistical Methods, Vol. 11, No. 1, 2012, p. 144-151.

Research output: Contribution to journalArticle

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