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Tolerance approach to possibilistic nonlinear regression with interval data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F14%3A10282632" target="_blank" >RIV/00216208:11320/14:10282632 - isvavai.cz</a>

  • Alternative codes found

    RIV/61384399:31140/14:00045593

  • Result on the web

    <a href="http://dx.doi.org/10.1109/TCYB.2014.2309596" target="_blank" >http://dx.doi.org/10.1109/TCYB.2014.2309596</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/TCYB.2014.2309596" target="_blank" >10.1109/TCYB.2014.2309596</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Tolerance approach to possibilistic nonlinear regression with interval data

  • Original language description

    We study possibilistic nonlinear regression models with crisp and/or interval data. Herein, the task is to compute tight interval regression parameters such that all observed output data (either crisp or interval) are covered by the range of the nonlinear interval regression function. We propose a method for determination of interval regression parameters based on the tolerance approach developed by the authors for the linear case. We define two classes of nonlinear regression models for which efficientalgorithms exist. For other models, we provide some extensions allowing to calculate lower and upper bounds on the widths of the optimal interval regression parameters. We also discuss other approaches to interval regression than the possibilistic one.We illustrate the theory by examples.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2014

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    IEEE Transactions on Cybernetics

  • ISSN

    2168-2267

  • e-ISSN

  • Volume of the periodical

    44

  • Issue of the periodical within the volume

    12

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    12

  • Pages from-to

    2509-2520

  • UT code for WoS article

  • EID of the result in the Scopus database