Poisson count time series

被引:0
|
作者
Kong, Jiajie [1 ]
Lund, Robert [1 ]
机构
[1] Univ Calif Santa Cruz, Dept Stat, Santa Cruz, CA 95064 USA
基金
美国国家科学基金会;
关键词
copulas; count time series; integer autoregression; Poisson distribution; superposition; thinning; BIVARIATE DISTRIBUTIONS; SELF-DECOMPOSABILITY; MARKOV-PROCESSES; EL-NINO; REGRESSION; SIMULATION; LIKELIHOOD; MIXTURES; MODEL;
D O I
10.1111/jtsa.12799
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This article reviews and compares popular methods, some old and some recent, that produce time series having Poisson marginal distributions. The article begins by narrating ways where time series with Poisson marginal distributions can be produced. Modeling nonstationary series with covariates motivates consideration of methods where the Poisson parameter depends on time. Here, estimation methods are developed for some of the more flexible methods. The results are used in the analysis of (1) a count sequence of tropical cyclones occurring in the North Atlantic Basin since 1970, and (2) the number of no-hitter games pitched in Major League Baseball since 1893. Tests for whether the Poisson marginal distribution is appropriate are included.
引用
收藏
页数:25
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