A flexible class of parametric transition regression models based on copulas: application to poliomyelitis incidence

DOI10.1177/0962280206070645zbMath1109.62076OpenAlexW2141479936WikidataQ51924304 ScholiaQ51924304MaRDI QIDQ3435348

Gabriel Escarela, Alberto Castillo-Morales, Ramsés H. Mena

Publication date: 26 April 2007

Published in: Statistical Methods in Medical Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/0962280206070645

zbMATH Keywords

diagnosticsbinary outcomesfirst-order discrete time stationary Markov process

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (6)

Copula-based regression models: a survey ⋮ Autoregressive density modeling with the Gaussian process mixture transition distribution ⋮ On Construction and Estimation of Stationary Mixture Transition Distribution Models ⋮ Count Time Series: A Methodological Review ⋮ Regression in a copula model for bivariate count data ⋮ Unnamed Item

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• Markov Poisson regression models for discrete time series. Part 1: Methodology
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