Modeling Zero Inflation in Count Data Time Series with Bounded Support
- Authors
- Moeller, Tobias A.; Weiss, Christian H.; Kim, Hee-Young; Sirchenko, Andrei
- Issue Date
- 6월-2018
- Publisher
- SPRINGER
- Keywords
- Binomial distribution; Count data time series; Hidden Markov model; Markov model; Zero inflation
- Citation
- METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY, v.20, no.2, pp.589 - 609
- Indexed
- SCIE
SCOPUS
- Journal Title
- METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY
- Volume
- 20
- Number
- 2
- Start Page
- 589
- End Page
- 609
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/75032
- DOI
- 10.1007/s11009-017-9577-0
- ISSN
- 1387-5841
- Abstract
- 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.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of Public Policy > Division of Big Data Science > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.