A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Bias correction for histogram estimator using line transect sampling
10.1002/env.671.abs
This article proposes a simple approach for reducing the bias of the traditional histogram estimator using line transect sampling. The approach uses the bias correction technique, which produces a new estimator for density of objects D. The proposed estimator reduces the bias from O(h2) to O(h3) as h → 0 under the shoulder condition assumption. The asymptotic properties of the proposed estimator are derived under some mild assumptions, and the optimal formula for the bin width is given. Small‐sample properties of the proposed estimator are studied and compared with some other existence estimators by using a simulation technique. The results show that improvements over the traditional histogram estimator often can be realized even at small or moderate sample size. Copyright © 2004 John Wiley & Sons, Ltd.
Bias correction for histogram estimator using line transect sampling
10.1002/env.671.abs
This article proposes a simple approach for reducing the bias of the traditional histogram estimator using line transect sampling. The approach uses the bias correction technique, which produces a new estimator for density of objects D. The proposed estimator reduces the bias from O(h2) to O(h3) as h → 0 under the shoulder condition assumption. The asymptotic properties of the proposed estimator are derived under some mild assumptions, and the optimal formula for the bin width is given. Small‐sample properties of the proposed estimator are studied and compared with some other existence estimators by using a simulation technique. The results show that improvements over the traditional histogram estimator often can be realized even at small or moderate sample size. Copyright © 2004 John Wiley & Sons, Ltd.
Bias correction for histogram estimator using line transect sampling
Eidous, Omar M. (author)
Environmetrics ; 16 ; 61-69
2005-02-01
9 pages
Article (Journal)
Electronic Resource
English
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