Variable-order Markov Model: Markov Chain, Markov Property, Andrey Markov, Probability Theory, Conditional Probability Distribution, Continuous-time Markov Process, Markov Process, Random Variable - Couverture souple

 
9786130335397: Variable-order Markov Model: Markov Chain, Markov Property, Andrey Markov, Probability Theory, Conditional Probability Distribution, Continuous-time Markov Process, Markov Process, Random Variable
Couverture souple
ISBN 10 : 6130335393 ISBN 13 : 9786130335397
Editeur : Betascript Publishing, 2010

Synopsis

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Variable-order Markov models are an important class of models that extend the well known Markov chain models. In contrast to the Markov chain models, where each random variable in a sequence with a Markov property depends on a fixed number of random variables, in VOM models this number of conditioning random variables may vary based on the specific observed realization. This realization sequence is often called the context; therefore the VOM models are also called context trees. The flexibility in the number of conditioning random variables turns out to be of real advantage for many applications, such as statistical analysis, classification and prediction.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Variable-order Markov models are an important class of models that extend the well known Markov chain models. In contrast to the Markov chain models, where each random variable in a sequence with a Markov property depends on a fixed number of random variables, in VOM models this number of conditioning random variables may vary based on the specific observed realization. This realization sequence is often called the context; therefore the VOM models are also called context trees. The flexibility in the number of conditioning random variables turns out to be of real advantage for many applications, such as statistical analysis, classification and prediction.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Betascript Publishing
Date d'édition
2010
Langue
anglais
ISBN 10 
6130335393
ISBN 13 
9786130335397
Reliure
Broché
Nombre de pages
80
Éditeur
Surhone Lambert M., Timpledon Miriam T., Marseken Susan F.
Coordonnées du fabricant
non disponible
Personne responsable
non disponible