Estimation in independent observer line transect surveys for clustered populations.
This paper introduces a framework for animal abundance estimation in independent observer line transect surveys of clustered populations. The framework generalizes an approach given in Chen (1999, Environmental and Ecological Statistics 6, in press) to accommodate heterogeneity in detection caused by cluster size and other covariates. Both parametric and nonparametric estimators for the local effective search widths, given the covariates, can be derived from the framework. A nonparametric estimator based on conditional kernel density estimation is proposed and studied owing to its flexibility in modeling the detection functions. A real data set on harbor porpoise in the North Sea is analyzed.
Chen
S X
SX
Department of Statistical Science, La Trobe University, Victoria, Australia. song.chen@latrobe.edu.au
D000818:Animals; D001699:Biometry; D016000:Cluster Analysis; D003625:Data Collection; D016013:Likelihood Functions; D011156:Population Density; D019576:Porpoises