Improved estimation of site occupancy using penalized likelihood
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Updated: Jun 13, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Monica Moreno1, Subhash R Lele
1Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB T6G 2G1, Canada. mmoreno@ualberta.ca
Abstract:
When detection or occupancy probability is small or when the number of sites and number of visits per site is small, maximum likelihood estimators (MLE) of site occupancy parameters have large biases, are numerically unstable, and the corresponding confidence intervals have smaller than nominal coverage. We propose an alternative method of estimation, based on penalized likelihood. This method is numerically stable, the estimators have smaller mean square error than the MLE, and associated confidence intervals have close to nominal coverage.
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