Robustified Total Least Squares estimators and their evaluations

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F15%3A00304796" target="_blank" >RIV/68407700:21340/15:00304796 - 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

Robustified Total Least Squares estimators and their evaluations

Original language description

Classical robust regression estimators, such as Least Trimmed Squares, are not consistent in error-in-variables models, where the explanatory variables are measured with a random error. The most frequent approaches in such a cases are Instrumental Variables and Total Least Squares estimation. This ontribution deals with robustification of Total Least Squares and present methods based on the idea of trimming, or downweighting of the influential points. Three different ways how to evaluate them are described and the accuracy of fast resampling algorithm is discussed and compared to two exact algorithms inspired by Branch-and-Bound and Borders Scanning Algorithms.

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

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2015

Confidentiality

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

Name of the periodical

Forum Statisticum Slovacum

ISSN

1336-7420

e-ISSN

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Volume of the periodical

XI

Issue of the periodical within the volume

6

Country of publishing house

SK - SLOVAKIA

Number of pages

8

Pages from-to

54-61

UT code for WoS article

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EID of the result in the Scopus database

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