Stochastic Algorithms in Nonlinear Regression

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F00%3A00000034" target="_blank" >RIV/61988987:17310/00:00000034 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Stochastic Algorithms in Nonlinear Regression

Original language description

This paper deals with the use of two stochastic algorithms (modified controlled random search and evolutionary search) in estimating the parameters of nonlinear regression models. The algorithms are experimentally tested on a set of the well-known taskschosen insuch way that most classical techniques based on objective function derivatives fail while treating them. The basic features of the algorithms (rate of convergence and reliability) as wel as their applicability to nonlinear regression models arediscussed in more detail

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BB - Applied statistics, operational research

OECD FORD branch

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Project

<a href="/en/project/GA402%2F00%2F1165" target="_blank" >GA402/00/1165: Modelling of the Regional Labour Market Development</a><br>

Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2000

Confidentiality

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

Name of the periodical

Computational Statistics & Data Analysis

ISSN

0167-9473

e-ISSN

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Volume of the periodical

33

Issue of the periodical within the volume

3

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

13

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

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