Predicting future discoveries of European marine species by using a non-homogeneous renewal process

被引:36
作者
Wilson, SP [1 ]
Costello, MJ
机构
[1] Univ Dublin Trinity Coll, Dept Stat, Dublin 2, Ireland
[2] Univ Auckland, Warkworth, New Zealand
[3] Ecole Polytech, Mecan Solides Lab, F-91128 Palaiseau, France
[4] Duke Univ, Inst Stat & Decis Sci, Durham, NC 27706 USA
关键词
Bayesian inference; dispersion; diversity; renewal process; reversible jump; species; thinned point process;
D O I
10.1111/j.1467-9876.2005.00513.x
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Predicting future rates of species discovery and the number of species remaining are important in efforts to preserve biodiversity, discussions on the rate of species extinction and comparisons on the state of knowledge of animals and plants of different taxa. Data on discovery dates of species in 32 European marine taxa are analysed by using a class of thinned temporal renewal process models. These models allow for both underdispersion and overdispersion with respect to the non-homogeneous Poisson process. An approach for implementing Bayesian inference for these models is described that uses Markov chain Monte Carlo simulation and that is applicable to other types of thinned process. Predictions are made on the number of species remaining to be discovered in each taxon.
引用
收藏
页码:897 / 918
页数:22
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