On Guaranteed Sequential Change Point Detection for TAR(1)/ARCH(1) Process

Yulia Burkatovskaya, Ekaterina Sergeeva, Sergei Vorobeychikov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The problem of guaranteed parameter estimation and change point detection of threshold autoregressive processes with conditional heteroscedasticity (TAR/ARCH) is considered. The parameters of the process are assumed to be unknown. A sequential procedure with guaranteed quality is proposed. The results of simulation are presented.

Original languageEnglish
Title of host publicationCommunications in Computer and Information Science
PublisherSpringer Verlag
Pages59-68
Number of pages10
Volume487
ISBN (Print)9783319136707
DOIs
Publication statusPublished - 2014
Event13th International Scientific Conference on Information Technologies and Mathematical Modelling, ITMM 2014 - Anzhero-Sudzhensk, Russian Federation
Duration: 20 Nov 201422 Nov 2014

Publication series

NameCommunications in Computer and Information Science
Volume487
ISSN (Print)18650929

Other

Other13th International Scientific Conference on Information Technologies and Mathematical Modelling, ITMM 2014
CountryRussian Federation
CityAnzhero-Sudzhensk
Period20.11.1422.11.14

Keywords

  • change point detection
  • guaranteed parameter estimation
  • TAR/ARCH

ASJC Scopus subject areas

  • Computer Science(all)

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  • Activities

    • 1 Participation in conference

    The International MultiConference of Engineers and Computer Scientists

    Yulia Borisovna Burkatovskaya (Participant), & Andrey Vladimirovich Proskokov (Participant)

    16 Mar 201618 Mar 2016

    Activity: Participating in or organising an event typesParticipation in conference

    Cite this

    Burkatovskaya, Y., Sergeeva, E., & Vorobeychikov, S. (2014). On Guaranteed Sequential Change Point Detection for TAR(1)/ARCH(1) Process. In Communications in Computer and Information Science (Vol. 487, pp. 59-68). (Communications in Computer and Information Science; Vol. 487). Springer Verlag. https://doi.org/10.2147/PPA.S72004