State space mixed models for binary responses with scale mixture of normal distributions links

DOI10.1016/J.CSDA.2013.01.009zbMath1471.62007OpenAlexW2052817117MaRDI QIDQ1621307

Carlos A. Abanto-Valle, Dey, Dipak K.

Publication date: 8 November 2018

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

Full work available at URL: https://doi.org/10.1016/j.csda.2013.01.009

zbMATH Keywords

longitudinal dataMarkov chain Monte Carlostate space modelssequential Monte Carloprobitparticle learningbinary time seriesscale mixture of normal links

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15)

Related Items (6)

Posterior property of Student-\(t\) linear regression model using objective priors ⋮ Efficient data augmentation techniques for some classes of state space models ⋮ A Dynamic Binary Probit Model with Time-Varying Parameters and Shrinkage Prior ⋮ Bayesian state-space modeling in gene expression data analysis: an application with biomarker prediction ⋮ Discrete-response state space models with conditional heteroscedasticity: an application to forecasting the federal funds rate target ⋮ Modelling financial time series based on heavy-tailed market microstructure models with scale mixtures of normal distributions

Uses Software

• Scythe

Cites Work

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