Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB T6G 2G1, Canada.
Ecology. 2010 Feb;91(2):341-6. doi: 10.1890/09-1073.1.
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.
当检测或占有概率较小时,或者当站点数量和每个站点的访问次数较小时,站点占有参数的最大似然估计(MLE)具有较大的偏差、数值不稳定,并且相应的置信区间的覆盖范围小于名义值。我们提出了一种基于惩罚似然的替代估计方法。这种方法数值稳定,估计量的均方误差小于 MLE,并且相关的置信区间接近名义覆盖范围。