On binary and categorical time series models with feedback

Moysiadis, T. and Fokianos, K. (2014) On binary and categorical time series models with feedback. Journal of Multivariate Analysis, 131. pp. 209-228. ISSN 0047-259X

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Abstract

We study the problem of ergodicity, stationarity and maximum likelihood estimation for multinomial logistic models that include a latent process. Our work includes various models that have been proposed for the analysis of binary and, more general, categorical time series. We give verifiable ergodicity and stationarity conditions for the analysis of such time series data. In addition, we study maximum likelihood estimation and prove that, under mild conditions, the estimator is asymptotically normally distributed. These results are applied to real and simulated data.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Multivariate Analysis
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2612
Subjects:
?? AUTOCORRELATIONCATEGORICAL DATAHIDDEN MARKOV MODELSLATENT PROCESSLOGISTIC REGRESSIONMULTINOMIAL REGRESSIONNOMINAL DATAPREDICTIONWEAK DEPENDENCESTATISTICS AND PROBABILITYSTATISTICS, PROBABILITY AND UNCERTAINTYNUMERICAL ANALYSIS ??
ID Code:
127761
Deposited By:
Deposited On:
26 Sep 2018 08:00
Refereed?:
Yes
Published?:
Published
Last Modified:
18 Sep 2023 01:26