State space mixed models for binary responses with scale mixture of normal distributions links
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DOI: 10.1016/j.csda.2013.01.009
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Cited by:
- Shuaimin Kang & Guangying Liu & Howard Qi & Min Wang, 2018. "Bayesian Variance Changepoint Detection in Linear Models with Symmetric Heavy-Tailed Errors," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 459-477, August.
- Chénangnon Frédéric Tovissodé & Aliou Diop & Romain Glèlè Kakaï, 2021. "Inference in skew generalized t-link models for clustered binary outcome via a parameter-expanded EM algorithm," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-31, April.
- Dimitrakopoulos, Stefanos & Dey, Dipak K., 2017. "Discrete-response state space models with conditional heteroscedasticity: An application to forecasting the federal funds rate target," Economics Letters, Elsevier, vol. 154(C), pages 20-23.
- Wang, Min & Yang, Mingan, 2016. "Posterior property of Student-t linear regression model using objective priors," Statistics & Probability Letters, Elsevier, vol. 113(C), pages 23-29.
- Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.
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Keywords
Binary time series; Longitudinal data; Markov chain Monte Carlo; Particle learning; Probit; Scale mixture of normal links; Sequential Monte Carlo; State space models;All these keywords.
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