A Spectral Estimator of Arma Parameters from Thresholded Data
Statistics and Computing
Preface: Special Issue on Nonlinear Modelling and Financial Econometrics
Computational Statistics & Data Analysis
Regression models for binary time series with gaps
Computational Statistics & Data Analysis
On weighting of bivariate margins in pairwise likelihood
Journal of Multivariate Analysis
Pairwise likelihood estimation for multivariate mixed Poisson models generated by Gamma intensities
Statistics and Computing
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Ordinal categorical time series may be analyzed as censored observations from a suitable latent stochastic process, which describes the underlying evolution of the system. This approach may be considered as an alternative to Markov chain models or to regression methods for categorical time series data. The problem of parameter estimation is solved through a simple pseudolikelihood, called pairwise likelihood. This inferential methodology is successfully applied to the class of autoregressive ordered probit models. Potential usefulness for inference and model selection within more general classes of models are also emphasized. Illustrations include simulation studies and two simple real data applications.