Algorithms and Programs of Dynamic Mixture Estimation. Unified Approach to Different Types of Components

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00477300" target="_blank" >RIV/67985556:_____/17:00477300 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-319-64671-8" target="_blank" >http://dx.doi.org/10.1007/978-3-319-64671-8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-64671-8" target="_blank" >10.1007/978-3-319-64671-8</a>

Result language

angličtina

Original language name

Algorithms and Programs of Dynamic Mixture Estimation. Unified Approach to Different Types of Components

Original language description

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.

Czech name

—

Czech description

—

Type

B - Specialist book

CEP classification

—

OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/GA15-03564S" target="_blank" >GA15-03564S: Clustering and classification using recursive mixture estimation</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

ISBN

978-3-319-64670-1

Number of pages

113

Publisher name

Springer

Place of publication

Cham

UT code for WoS book

000446970800007