A weighted exponential detection function model for line transect data

Faisal Ababneh*, Omar M. Eidous

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 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
DOIs
Publication statusPublished - 2012
Externally publishedYes

Keywords

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

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Fingerprint

Dive into the research topics of 'A weighted exponential detection function model for line transect data'. Together they form a unique fingerprint.

Cite this