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Forecasting of Discrete Time Series

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Robustness in Statistical Forecasting

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Abstract

This chapter is devoted to forecasting in the non-classical setting where the state space of the time series is finite, necessitating the use of discrete-valued time series models. The field of discrete statistics has remained relatively underdeveloped until the recent years, when rapid introduction of digital equipment stimulated the researchers to develop numerous discrete models and techniques. In this chapter, we discuss optimal forecasting statistics and forecast risks for Markov chain models, including high-order Markov chains, and the beta-binomial model.

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Authors and Affiliations

  1. Department of Mathematical Modeling and Data Analysis, Belarusian State University, Minsk, Belarus

    Yuriy Kharin

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  1. Yuriy Kharin
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Kharin, Y. (2013). Forecasting of Discrete Time Series. In: Robustness in Statistical Forecasting. Springer, Cham. https://doi.org/10.1007/978-3-319-00840-0_10

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