Modeling Zero Inflation in Count Data Time Series with Bounded Support

被引：33

作者：

Moeller, Tobias A. ^{[1
]}

Weiss, Christian H. ^{[1
]}

Kim, Hee-Young ^{[2
]}

Sirchenko, Andrei ^{[3
]}

机构：

[1] Helmut Schmidt Univ, Dept Math & Stat, Hamburg, Germany

[2] Korea Univ, Div Econ & Stat, Natl Stat, Sejong, South Korea

[3] Higher Sch Econ, Dept Econ, Moscow, Russia

来源：

METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY | 2018年 / 20卷 / 02期

关键词：

Binomial distribution; Count data time series; Hidden Markov model; Markov model; Zero inflation; POISSON;

D O I：

10.1007/s11009-017-9577-0

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：

Real count data time series often show an excessive number of zeros, which can form quite different patterns. We develop four extensions of the binomial autoregressive model for autocorrelated counts with a bounded support, which can accommodate a broad variety of zero patterns. The stochastic properties of these models are derived, and ways of parameter estimation and model identification are discussed. The usefulness of the models is illustrated, among others, by an application to the monetary policy decisions of the National Bank of Poland.

引用

页码：589 / 609

页数：21

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