On sensitivity of posterior inference to various priors in population size estimation through capture-recapture method - a simulation study
Date Issued
2006
Date
2006
Author(s)
Chang, Chia-Hui
DOI
zh-TW
Abstract
Ecologists study populations for many reasons. Population studies hold the key to saving endangered species, controlling pest populations, and managing game populations. They also offer clues to understanding and controlling disease epidemics.
Finally, the greatest environmental challenge to biological diversity and the integrity of the entire biosphere is at its heart a population problem.
Bayesian inference was introduced to the wild life population size estimation in the early 1980. Through the years statisticians keep putting efforts on incorporating the Bayesian way of estimation into the well-known capture-mark-recapture method.
Though the progress in this area of research is achieved, there are still some questions unanswered. One of them is the magnitude of impact caused by various priors on the sensitivity of posterior inference. The author tries to approach this question by simulation study. Two different scenarioes are set for the simulation study; one is for large number of recaptures; the other less number of recaptures. The results show that number of recaptures are critical to the sensitivity of posterior inference. Large variation of posterior mean is associated with large number of recaptures while the number of recaptures is small the corresponding variation is also reduced.
Subjects
貝氏推論
重複捕取模式
無訊息先驗分布
共軛先驗分布
最大後驗密度可信區間
Bayesian inference
capture-recapture model
noninformative prior distribution
conjugate prior distribution
HPD
Type
thesis
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