On binary and categorical time series models with feedback

DOI10.1016/j.jmva.2014.07.004zbMath1298.62155arXiv1504.06185OpenAlexW2025045431MaRDI QIDQ406539

Theodoros Moysiadis, Konstantinos Fokianos

Publication date: 8 September 2014

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1504.06185

zbMATH Keywords

predictionlogistic regressionhidden Markov modelsautocorrelationweak dependencelatent processcategorical datanominal datamultinomial regression

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Generalized linear models (logistic models) (62J12)

Related Items (12)

Nonparametric estimation of dynamic discrete choice models for time series data ⋮ A Bernoulli autoregressive moving average model applied to rainfall occurrence ⋮ Modeling normalcy‐dominant ordinal time series: An application to air quality level ⋮ Strong mixing properties of discrete-valued time series with exogenous covariates ⋮ Generalized autoregressive moving average models: an efficient estimation approach ⋮ Forecasting binary outcomes in soccer ⋮ Stationarity and ergodic properties for some observation-driven models in random environments ⋮ On categorical time series models with covariates ⋮ Robust estimation for binomial conditionally nonlinear autoregressive time series based on multivariate conditional frequencies ⋮ Statistical analysis of multivariate discrete-valued time series ⋮ Local stationarity and time-inhomogeneous Markov chains ⋮ Multivariate time series models for mixed data

Uses Software

• R
• Fahrmeir

Cites Work

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