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Detection of similar successive groups in a model with diverging number of variable groups

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10419912" target="_blank" >RIV/00216208:11320/20:10419912 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=uu5jxgJ1vB" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=uu5jxgJ1vB</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1080/07474946.2020.1726687" target="_blank" >10.1080/07474946.2020.1726687</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Detection of similar successive groups in a model with diverging number of variable groups

  • Original language description

    In this article, a linear model with grouped explanatory variables is considered. The idea is to perform an automatic detection of different successive groups of the unknown coefficients under the assumption that the number of groups is of the same order as the sample size. The standard least squares loss function and the quantile loss function are both used together with the fused and adaptive fused penalty to simultaneously estimate and group the unknown parameters. The proper convergence rate is given for the obtained estimators and the upper bound for the number of different successive group is derived. A simulation study is used to compare the empirical performance of the proposed fused and adaptive fused estimators, and a real application on the air quality data demonstrates the practical applicability of the proposed methods.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

    <a href="/en/project/GJ18-00522Y" target="_blank" >GJ18-00522Y: Advanced Econometric Models for Option Pricing – AdEMOP</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2020

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Sequential Analysis

  • ISSN

    0747-4946

  • e-ISSN

  • Volume of the periodical

    39

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    23

  • Pages from-to

    92-114

  • UT code for WoS article

    000532639000006

  • EID of the result in the Scopus database

    2-s2.0-85084832257