Pairwise likelihood inference for ordinal categorical time series

DOI10.1016/j.csda.2006.09.009zbMath1157.62499OpenAlexW2078486342MaRDI QIDQ1010578

Paolo Vidoni, Cristiano Varin

Publication date: 6 April 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.09.009

zbMATH Keywords

model selectiontime seriespairwise likelihoodquantized dataordinal categorical dataalofi dataOxford-Cambridge boat race data

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Nonparametric estimation (62G05)

Related Items

Pairwise likelihood ratio tests and model selection criteria for structural equation models with ordinal variables ⋮ Mixture models for ordinal data: a pairwise likelihood approach ⋮ A note on predictive densities based on composite likelihood methods ⋮ Time series analysis of categorical data using auto-mutual information ⋮ Composite Likelihood Estimation of an Autoregressive Panel Ordered Probit Model with Random Effects ⋮ Analysis of dependent data aggregated into intervals ⋮ Composite likelihood estimation for a Gaussian process under fixed domain asymptotics ⋮ On composite marginal likelihoods ⋮ Pairwise Likelihood Inference for General State Space Models ⋮ On weighting of bivariate margins in pairwise likelihood ⋮ Regression models for binary time series with gaps ⋮ Sampling of pairs in pairwise likelihood estimation for latent variable models with categorical observed variables

Uses Software

• R
• Fahrmeir

Cites Work

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