Prediction and Classification of Non-stationary Categorical Time Series
Date
1998ISSN
0047-259XSource
Journal of Multivariate AnalysisVolume
67Issue
2Pages
277-296Google Scholar check
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Partial likelihood analysis of a general regression model for the analysis of non-stationary categorical time series is presented, taking into account stochastic time dependent covariates. The model links the probabilities of each category to a covariate process through a vector of time invariant parameters. Under mild regularity conditions, we establish good asymptotic properties of the estimator by appealing to martingale theory. Certain diagnostic tools are presented for checking the adequacy of the fit. © 1998 Academic Press.