Sequential Monitoring for Detection of Breaks in Panel Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10506668" target="_blank" >RIV/00216208:11320/25:10506668 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-92383-8_32" target="_blank" >https://doi.org/10.1007/978-3-031-92383-8_32</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-92383-8_32" target="_blank" >10.1007/978-3-031-92383-8_32</a>
Alternative languages
Result language
angličtina
Original language name
Sequential Monitoring for Detection of Breaks in Panel Data
Original language description
Procedures for the detection of changes in panel data typically concern offline procedures, i.e., all observations are available at the beginning of the statistical analysis and testing is done retrospectively. The present paper deals with online procedures for detecting a change in the mean of panel data arriving sequentially, with the total number of observations eventually received being random. The procedures are developed using principles of offline detection procedures [5] in combination with those used in online procedures [8]. Some limit properties of the proposed procedures are presented, as well as simulation results exhibiting desirable finite-sample properties. The focus is on high-dimensional panel models, which are high dimensional time series with special properties often encountered in econometrics and financial applications.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GA23-05737S" target="_blank" >GA23-05737S: Functional Fourier Data Analysis</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
NEW TRENDS IN FUNCTIONAL STATISTICS AND RELATED FIELDS
ISBN
978-3-031-92382-1
ISSN
1431-1968
e-ISSN
—
Number of pages
8
Pages from-to
259-266
Publisher name
SPRINGER INTERNATIONAL PUBLISHING AG
Place of publication
CHAM
Event location
Novara
Event date
Jun 25, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001545850800032