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Asymptotics of Two-boundary First-exit-time Densities for Gauss-Markov Processes

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985823%3A_____%2F19%3A00509186" target="_blank" >RIV/67985823:_____/19:00509186 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/article/10.1007%2Fs11009-018-9617-4" target="_blank" >https://link.springer.com/article/10.1007%2Fs11009-018-9617-4</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s11009-018-9617-4" target="_blank" >10.1007/s11009-018-9617-4</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Asymptotics of Two-boundary First-exit-time Densities for Gauss-Markov Processes

  • Original language description

    The problem of escape times from a region confined by two time-dependent boundaries is considered for a class of Gauss-Markov processes. Asymptotic approximations of the first exit time probability density functions in case of asymptotically constant and asymptotically periodic boundaries are obtained firstly for the Ornstein-Uhlenbeck process and then extended to the class of Gauss-Markov processes that can be obtained by a specified transformation. Some examples of application to stochastic dynamics and estimations of involved parameters by using numerical approximations are provided.

  • 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

    10102 - Applied mathematics

Result continuities

  • Project

    <a href="/en/project/GA17-06943S" target="_blank" >GA17-06943S: Neural coding precision and its adaptation to the stimulus statistics</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Methodology and Computing in Applied Probability

  • ISSN

    1387-5841

  • e-ISSN

  • Volume of the periodical

    21

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    18

  • Pages from-to

    735-752

  • UT code for WoS article

    000484932800006

  • EID of the result in the Scopus database

    2-s2.0-85040702094