Stochastic Matrix: Markov Chain, Matrix, Doubly Stochastic Matrix, Probability Vector, Euclidean Vector, Probability Space, Row Vector, Perron–Frobenius Theorem - Couverture souple

 
9786130362782: Stochastic Matrix: Markov Chain, Matrix, Doubly Stochastic Matrix, Probability Vector, Euclidean Vector, Probability Space, Row Vector, Perron–Frobenius Theorem
Couverture souple
ISBN 10 : 6130362781 ISBN 13 : 9786130362782
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. In mathematics, a stochastic matrix, probability matrix, or transition matrix is used to describe the transitions of a Markov chain. It has found use in probability theory, statistics and linear algebra, as well as computer science. There are several different definitions and types of stochastic matrices; A right stochastic matrix is a square matrix each of whose rows consists of nonnegative real numbers, with each row summing to 1. A left stochastic matrix is a square matrix whose columns consist of nonnegative real numbers whose sum is 1. A doubly stochastic matrix where all entries are nonnegative and all rows and all columns sum to 1.

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Éditeur
Betascript Publishing
Date d'édition
2010
Langue
anglais
ISBN 10 
6130362781
ISBN 13 
9786130362782
Reliure
Broché
Nombre de pages
92
Éditeur
Surhone Lambert M., Tennoe Mariam T., Henssonow Susan F.
Coordonnées du fabricant
non disponible
Personne responsable
non disponible