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Simulation study for robustness and consistency of minimum distance density estimates under physical data framework

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F12%3A00197408" target="_blank" >RIV/68407700:21340/12:00197408 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21240/12:00197408

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Simulation study for robustness and consistency of minimum distance density estimates under physical data framework

  • Original language description

    We are interested in consistency of these estimates and their robustness, as well as its impact to the physical data processing coming from an accelerated physics. We introduce a wide class of modifications of the Kolmogorov-Cramér distance by implementing data-based weight functions, random selecting of differences to be summed up, and using various coefficient modifications. All these new estimates are defined to preserve consistency and simultaneously to have better robust properties than the Kolmogorov estimate.We perform an extensive simulation study to compare robustness of newly introduced estimates with the original Kolmogorov and Cramér-von Mises estimates.

  • Czech name

  • Czech description

Classification

  • Type

    O - Miscellaneous

  • CEP classification

    BA - General mathematics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/LG12020" target="_blank" >LG12020: Advanced statistical analysis and non-statistical separation techniques for physical processing detection in data sets sampled by means of elementary particle accelerators.</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2012

  • Confidentiality

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