Abundance Estimation Using Minimum Order Set Distances in Line Transect Sampling

Line transect sampling is widely used for estimating population abundance, but existing nonparametric estimators of detection density at the transect line often suffer from boundary bias and tuning sensitivity. In this paper, we propose two simple tuning-light estimators based on minimum order statistics of perpendicular distances, requiring measurement of only the judged-closest object within each set. Under mild regularity conditions, the proposed estimators are consistent and asymptotically normal, with low bias and variance demonstrated through simulation studies under exponential and half-normal detection models. An application to a wooden stakes transect survey illustrates the practical advantages of the proposed approach for low-effort ecological surveys.

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Publication Details

Journal
Stats
Published
2026-02-26
DOI
https://doi.org/10.3390/stats9020022
Primary Topic
Survey Sampling and Estimation Techniques
Type
article
Field-Weighted Citation Impact
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article

Abundance Estimation Using Minimum Order Set Distances in Line Transect Sampling

M. A. Al Kadiri, Mariam Al-Husari
Stats
Survey Sampling and Estimation Techniques
article

Abundance Estimation Using Minimum Order Set Distances in Line Transect Sampling

M. A. Al Kadiri, Mariam Al-Husari
article en

Abstract

Line transect sampling is widely used for estimating population abundance, but existing nonparametric estimators of detection density at the transect line often suffer from boundary bias and tuning sensitivity. In this paper, we propose two simple tuning-light estimators based on minimum order statistics of perpendicular distances, requiring measurement of only the judged-closest object within each set. Under mild regularity conditions, the proposed estimators are consistent and asymptotically normal, with low bias and variance demonstrated through simulation studies under exponential and half-normal detection models. An application to a wooden stakes transect survey illustrates the practical advantages of the proposed approach for low-effort ecological surveys.

StatsVol. 9(2)
Yarmouk University (JO)
Openalex Percentile: Top 45%
Survey Sampling and Estimation Techniques
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