Testing for an excessive number of zeros in time series of bounded counts
- Authors
- Kim, Hee-Young; Weiss, Christian H.; Moeller, Tobias A.
- Issue Date
- 12월-2018
- Publisher
- SPRINGER HEIDELBERG
- Keywords
- Binomial AR(1) model; Binomial index of dispersion; Binomial zero index; Extra-binomial dispersion; Extra-binomial zeros; Adjusted sample size
- Citation
- STATISTICAL METHODS AND APPLICATIONS, v.27, no.4, pp.689 - 714
- Indexed
- SCIE
SCOPUS
- Journal Title
- STATISTICAL METHODS AND APPLICATIONS
- Volume
- 27
- Number
- 4
- Start Page
- 689
- End Page
- 714
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/71274
- DOI
- 10.1007/s10260-018-00431-z
- ISSN
- 1618-2510
- Abstract
- For the modeling of bounded counts, the binomial distribution is a common choice. In applications, however, one often observes an excessive number of zeros and extra-binomial variation, which cannot be explained by a binomial distribution. We propose statistics to evaluate the number of zeros and the dispersion with respect to a binomial model, which is based on the sample binomial index of dispersion and the sample binomial zero index. We apply this index to autocorrelated counts generated by a binomial autoregressive process of order one, which also includes the special case of independent and identically (i.i.d.) bounded counts. The limiting null distributions of the proposed test statistics are derived. A Monte-Carlo study evaluates their size and power under various alternatives. Finally, we present two real-data applications as well as the derivation of effective sample sizes to illustrate the proposed methodology.
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Collections - College of Public Policy > Division of Big Data Science > 1. Journal Articles
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