Computational possibilities and properties of robustified version of the mixed Least Squares - Total Least Squares estimator

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F12%3A00199819" target="_blank" >RIV/68407700:21340/12:00199819 - 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
Computational possibilities and properties of robustified version of the mixed Least Squares - Total Least Squares estimator
Original language description
Classical robust regression estimators, such as Least Trimmed Squares (LTS), are not consistent when both independent and some dependent variables are considered to be measured with a random error. One way how to cope with this problem is to use the robustified version of Mixed Least Squares - Total Least Squares (LS-TLS). Mixed Least Trimmed Squares - Total Least Trimmed Squares (LTS-TLTS) based on trimming and mixed Least Weighted Squares - Total Least Weighted Squares (LWS-TLWS) based on the idea ofdownweighting the influential points, are proposed. The existence and uniqueness of the solution, breakdown point, consistency and another properties of these estimators are discussed. Different approaches of calculation, such as Branch-and-Bound algorithm, elemental concentration algorithm and simulated annealing, are described and their performances are shown on sets of benchmark instances.
Czech name
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Czech description
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Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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