期刊
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
卷 96, 期 455, 页码 915-923出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/016214501753208618
关键词
Bayes theorem; hierarchical models; Markov chain Monte Carlo; random curves
We address estimating fetal growth and gestation for bowhead whales of the Bering, Chukchi, and Beaufort seas stock. This population is subject to a subsistence hunt by Eskimo whale hunters, which is monitored via a quota system established by the International Whaling Commission. Quota determination is assisted by biological information, such as fetal growth and gestation, which is the basis of a population dynamics model used to estimate the annual replacement yield of the stock. We developed a Bayesian hierarchical nonlinear model for fetal growth with computation carried out via Markov chain Monte Carlo techniques. Our model allows for unique conception and parturition dates and provides predictive distributions for gestation length and conception dates. These results are used to propose estimates of geographic locations for conception and parturition. A sensitivity analysis indicated caution when specifying some hyperparameters related to growth rate, conception dates, and parturition dates.
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