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
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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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
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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