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Sinopsis
Explicit-Duration Markov Switching Models provides a simple and clear description of explicit-duration modeling by categorizing the different approaches into three main groups, which differ in encoding in the explicit-duration variables different information about regime switching/reset boundaries. The approaches are described using the formalism of graphical models, which enables graphical representation and assessment of statistical dependence, and therefore makes it easy to describe the structure of complex models and derive inference routines. The presentation is pedagogical, focusing on making distinctions that help structure the space of models and in laying out inference and learning in a clear way. Explicit-Duration Markov Switching Models is an ideal reference for students and researchers who wish to learn about these models and those looking to develop them further.
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Reseña del editor
Explicit-Duration Markov Switching Models provides a simple and clear description of explicit-duration modeling by categorizing the different approaches into three main groups, which differ in encoding in the explicit-duration variables different information about regime switching/reset boundaries. The approaches are described using the formalism of graphical models, which enables graphical representation and assessment of statistical dependence, and therefore makes it easy to describe the structure of complex models and derive inference routines. The presentation is pedagogical, focusing on making distinctions that help structure the space of models and in laying out inference and learning in a clear way. Explicit-Duration Markov Switching Models is an ideal reference for students and researchers who wish to learn about these models and those looking to develop them further.
Reseña del editor
Time-series are often modelled probabilistically as sequences of segments using first-order Markovian hidden variables representing different dynamics regimes. Such dynamics-regime variables implicitly define a geometric segment-duration distribution. A more flexible distribution requires introducing extra variables into the model with increased computational cost. This can be achieved in different ways, whose properties and categorization are still unclear. This book describes in a simple way different approaches to modelling the segment-duration distribution by categorizing them into three main groups, differing respectively by explicitly encoding information about segment beginning, end and both beginning and end by means of different segment-duration variables and associated distributions. The approaches are described using the framework of belief networks, which makes it possible to visually and therefore easily describe model structure and assess independence among random variables. This description enables a simple and clear understanding of approaches and inference routines in the literature but also to gain new insights especially about models with complex hidden variables.
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A Simple Tutorial on Hidden Markov Switching Models With Explicit Segment-Duration Distribution (Foundations and Trends in Machine Learning)
Librería: Books Puddle, New York, NY, Estados Unidos de America
Calificación del vendedor: 4 de 5 estrellas
Condición: New. 75. Nº de ref. del artículo: 26372220528
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Explicit-Duration Markov Switching Models (Foundations and Trends (R) in Machine Learning): 24 (Foundations and Trends® in Machine Learning) [Paperback] Chiappa, Silvia
Publicado por
Now Publishers, 2014
ISBN 10: 1601988303
ISBN 13: 9781601988300
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Librería: Hay-on-Wye Booksellers, Hay-on-Wye, HEREF, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: Very Good. Unused, some outer edges have minor scuffs, cover has light scratches, some outer pages have marks from shelf wear, book content is in like new condition. Nº de ref. del artículo: 101242-3
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A Simple Tutorial on Hidden Markov Switching Models With Explicit Segment-Duration Distribution (Foundations and Trends in Machine Learning)
Impresión bajo demandaLibrería: Majestic Books, Hounslow, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Print on Demand 75. Nº de ref. del artículo: 374873519
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A Simple Tutorial on Hidden Markov Switching Models With Explicit Segment-Duration Distribution (Foundations and Trends in Machine Learning)
Impresión bajo demandaLibrería: Biblios, Frankfurt am main, HESSE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: New. PRINT ON DEMAND 75. Nº de ref. del artículo: 18372220538
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EUR 9,95
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