Markov Chain Approach to Forecast in the Binomial Autoregressive ModelsMarkov Chain Approach to Forecast in the Binomial Autoregressive Models
- Other Titles
- Markov Chain Approach to Forecast in the Binomial Autoregressive Models
- Authors
- 김희영; 박유성
- Issue Date
- 2010
- Publisher
- 한국통계학회
- Keywords
- Binomial thinning; binomial AR(p) model; Markov chain
- Citation
- Communications for Statistical Applications and Methods, v.17, no.3, pp.441 - 450
- Indexed
- KCI
- Journal Title
- Communications for Statistical Applications and Methods
- Volume
- 17
- Number
- 3
- Start Page
- 441
- End Page
- 450
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/117614
- ISSN
- 2287-7843
- Abstract
- In this paper we consider the problem of forecasting binomial time series, modelled by the binomial autoregressive model. This paper considers proposed by Bu and McCabe (2008) and is extended to a higher order by Weib (2009).
Since the binomial autoregressive model is a Markov chain,we can apply the earlier work of Bu and McCabe (2008) for integer valued autoregressive(INAR) model to the binomial autoregressive model.
We will discuss how to compute the h-step-ahead forecast of the conditional probabilities of XT+h when T periods are used in fitting. Then we obtain the maximum likelihood estimator of binomial autoregressive model and use it to derive the maximum likelihood estimator of the h-step-ahead forecast of the conditional probabilities of XT+h.
The methodology is illustrated by applying it to a data set previously analyzed by Weib (2009).
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