Mixture and Hidden Markov Models with R

Author:   Ingmar Visser ,  Maarten Speekenbrink
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2022
ISBN:  

9783031014383


Pages:   267
Publication Date:   29 June 2022
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Mixture and Hidden Markov Models with R


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Author:   Ingmar Visser ,  Maarten Speekenbrink
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2022
Weight:   0.594kg
ISBN:  

9783031014383


ISBN 10:   3031014383
Pages:   267
Publication Date:   29 June 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Reviews

“The book is intended to guide the reader step by step on how to apply basic versions of FM and HM models and keep the text generally accessible to a broad audience, mainly from sociology, psychology, and economics, who have not used these models before and would apply them.” (Francesco Bartolucci and Fulvia Pennoni, Psychometrika, Vol. 89 (2), June, 2024)


Author Information

Ingmar Visser is Associate Professor of Developmental Psychology at the Department of Psychology, University of Amsterdam, where he also obtained his PhD after studying philosophy of language, mathematics and psychology. His research revolves around studying the dynamics of learning and development in all stages of development and in developing statistical methods for optimally mapping such development. Maarten Speekenbrink is Associate Professor of Mathematical Psychology at the Department of Experimental Psychology, University College London, and Fellow of the Alan Turing Institute, the UK national institute for data science and artificial intelligence. He obtained his PhD in Psychological Methods at the University of Amsterdam. Together, the authors developed the depmixS4 package, which already has a large user base in different areas of science. They have authored articles on the theory and use of hidden Markov models, and have given numerous talks and workshops on mixture and hidden Markov modelling.

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