{"title":"负二项过程模型中的广义Dickman分布和种数","authors":"Yuguang F. Ipsen, R. Maller, S. Shemehsavar","doi":"10.1017/apr.2020.61","DOIUrl":null,"url":null,"abstract":"Abstract We derive the large-sample distribution of the number of species in a version of Kingman’s Poisson–Dirichlet model constructed from an \n$\\alpha$\n -stable subordinator but with an underlying negative binomial process instead of a Poisson process. Thus it depends on parameters \n$\\alpha\\in (0,1)$\n from the subordinator and \n$r>0$\n from the negative binomial process. The large-sample distribution of the number of species is derived as sample size \n$n\\to\\infty$\n . An important component in the derivation is the introduction of a two-parameter version of the Dickman distribution, generalising the existing one-parameter version. Our analysis adds to the range of Poisson–Dirichlet-related distributions available for modeling purposes.","PeriodicalId":53160,"journal":{"name":"Advances in Applied Probability","volume":"53 1","pages":"370 - 399"},"PeriodicalIF":0.9000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/apr.2020.61","citationCount":"3","resultStr":"{\"title\":\"A generalised Dickman distribution and the number of species in a negative binomial process model\",\"authors\":\"Yuguang F. Ipsen, R. Maller, S. Shemehsavar\",\"doi\":\"10.1017/apr.2020.61\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract We derive the large-sample distribution of the number of species in a version of Kingman’s Poisson–Dirichlet model constructed from an \\n$\\\\alpha$\\n -stable subordinator but with an underlying negative binomial process instead of a Poisson process. Thus it depends on parameters \\n$\\\\alpha\\\\in (0,1)$\\n from the subordinator and \\n$r>0$\\n from the negative binomial process. The large-sample distribution of the number of species is derived as sample size \\n$n\\\\to\\\\infty$\\n . An important component in the derivation is the introduction of a two-parameter version of the Dickman distribution, generalising the existing one-parameter version. Our analysis adds to the range of Poisson–Dirichlet-related distributions available for modeling purposes.\",\"PeriodicalId\":53160,\"journal\":{\"name\":\"Advances in Applied Probability\",\"volume\":\"53 1\",\"pages\":\"370 - 399\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2021-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1017/apr.2020.61\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Applied Probability\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1017/apr.2020.61\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Applied Probability","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1017/apr.2020.61","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
A generalised Dickman distribution and the number of species in a negative binomial process model
Abstract We derive the large-sample distribution of the number of species in a version of Kingman’s Poisson–Dirichlet model constructed from an
$\alpha$
-stable subordinator but with an underlying negative binomial process instead of a Poisson process. Thus it depends on parameters
$\alpha\in (0,1)$
from the subordinator and
$r>0$
from the negative binomial process. The large-sample distribution of the number of species is derived as sample size
$n\to\infty$
. An important component in the derivation is the introduction of a two-parameter version of the Dickman distribution, generalising the existing one-parameter version. Our analysis adds to the range of Poisson–Dirichlet-related distributions available for modeling purposes.
期刊介绍:
The Advances in Applied Probability has been published by the Applied Probability Trust for over four decades, and is a companion publication to the Journal of Applied Probability. It contains mathematical and scientific papers of interest to applied probabilists, with emphasis on applications in a broad spectrum of disciplines, including the biosciences, operations research, telecommunications, computer science, engineering, epidemiology, financial mathematics, the physical and social sciences, and any field where stochastic modeling is used.
A submission to Applied Probability represents a submission that may, at the Editor-in-Chief’s discretion, appear in either the Journal of Applied Probability or the Advances in Applied Probability. Typically, shorter papers appear in the Journal, with longer contributions appearing in the Advances.