Book Review of Mixture and Hidden Markov Models with R by Visser & Speekenbrink
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11336-024-09958-5.pdf
Reference22 articles.
1. Bartolucci, F., Bacci, S., & Gnaldi, M. (2015). Statistical Analysis of Questionnaires: A Unified Approach Based on R and Stata. Chapman & Hall/CRC.
2. Bartolucci, F., Farcomeni, A., & Pennoni, F. (2013). Latent Markov Models for Longitudinal Data. Chapman & Hall/CRC Press.
3. Bartolucci, F., Pandolfi, S., & Pennoni, F. (2017). LMest: An R package for latent Markov models for longitudinal categorical data. Journal of Statistical Software, 81, 1–38.
4. Bouveyron, C., Celeux, G., Murphy, T. B., & Raftery, A. E. (2019). Model-Based Clustering and Classification for Data Science: With Applications in R. Cambridge University Press.
5. Ephraim, Y., & Merhav, N. (2002). Hidden Markov processes. IEEE Transactions on Information Theory, 48, 1518–1569.
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1. Correction: Book Review of Mixture and Hidden Markov Models with R, by Visser & Speekenbrink;Psychometrika;2024-07-31
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