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Algorithms and programs of dynamic m...

Nagy, Ivan.

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Algorithms and programs of dynamic mixture estimation = unified approach to different types of components /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Algorithms and programs of dynamic mixture estimation/ by Ivan Nagy, Evgenia Suzdaleva.
Reminder of title:	unified approach to different types of components /
Author:	Nagy, Ivan.
other author:	Suzdaleva, Evgenia.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	ix, 113 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Basic Models -- Statistical Analysis of Dynamic Mixtures -- Dynamic Mixture Estimation -- Program Codes -- Experiments -- Appendices.
Contained By:	Springer eBooks
Subject:	Estimation theory. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-64671-8
ISBN:	9783319646718

Algorithms and programs of dynamic mixture estimation = unified approach to different types of components /
Nagy, Ivan.

Algorithms and programs of dynamic mixture estimationunified approach to different types of components /[electronic resource] :by Ivan Nagy, Evgenia Suzdaleva. - Cham :Springer International Publishing :2017. - ix, 113 p. :ill., digital ;24 cm. - SpringerBriefs in statistics,2191-544X. - SpringerBriefs in statistics..

Introduction -- Basic Models -- Statistical Analysis of Dynamic Mixtures -- Dynamic Mixture Estimation -- Program Codes -- Experiments -- Appendices.

This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.

ISBN: 9783319646718

Standard No.: 10.1007/978-3-319-64671-8doiSubjects--Topical Terms:

565962
Estimation theory.

LC Class. No.: QA276.8 / .N34 2017

Dewey Class. No.: 519.544

Algorithms and programs of dynamic mixture estimation = unified approach to different types of components /
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100 1 $a Nagy, Ivan. $3 3252296
245 1 0 $a Algorithms and programs of dynamic mixture estimation $h [electronic resource] : $b unified approach to different types of components / $c by Ivan Nagy, Evgenia Suzdaleva.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a ix, 113 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in statistics, $x 2191-544X
505 0 $a Introduction -- Basic Models -- Statistical Analysis of Dynamic Mixtures -- Dynamic Mixture Estimation -- Program Codes -- Experiments -- Appendices.
520 $a This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.
650 0 $a Estimation theory. $3 565962
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650 2 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Systems Theory, Control. $3 893834
650 2 4 $a Simulation and Modeling. $3 890873
650 2 4 $a Algorithms. $3 536374
700 1 $a Suzdaleva, Evgenia. $3 3252297
710 2 $a SpringerLink (Online service) $3 836513
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830 0 $a SpringerBriefs in statistics. $3 1565658
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-64671-8
950 $a Mathematics and Statistics (Springer-11649)