Artikel
Detecting relevant changes in the spatiotemporal mean function
For a spatiotemporal process {Xj(s,t)∣s∈S,t∈T}j=1,…,n, where S denotes the set of spatial locations and T the time domain, we consider the problem of testing for a change in the sequence of mean functions {μj(s,t)∣s∈S,t∈T}j=1,…,n. In contrast to most of the literature, we are not interested in arbitrarily small changes but only in changes with a norm exceeding a given threshold. Asymptotically distribution free tests are proposed, which do not require the estimation of the long‐run spatiotemporal covariance structure. In particular, we consider a fully functional approach and a test based on the cumulative sum paradigm, investigate the large sample properties of the corresponding test statistics and study their finite sample properties by means of simulation study.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Journal of Time Series Analysis ; ISSN: 1467-9892 ; Volume: 44 ; Year: 2023 ; Issue: 5-6 ; Pages: 505-532 ; Oxford, UK: John Wiley & Sons, Ltd
- Thema
-
Spatiotemporal process
functional data analysis
change point analysis
self‐normalization
relevant hypotheses
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Dette, Holger
Quanz, Pascal
- Ereignis
-
Veröffentlichung
- (wer)
-
John Wiley & Sons, Ltd
- (wo)
-
Oxford, UK
- (wann)
-
2023
- DOI
-
doi:10.1111/jtsa.12674
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Dette, Holger
- Quanz, Pascal
- John Wiley & Sons, Ltd
Entstanden
- 2023
Ähnliche Objekte (12)
Canonical moments, orthogonal polynomials with application to statistics
On robust and efficient designs for risk estimation in epidemiologic studies
Strong approximation of eigenvalues of large dimensional Wishart matrices by roots of generalized Laguerre polynomials
Detecting deviations from stationarity
Detecting changes in the mean and variance of a time series : an approach based on U-statistics of triangular arrays
Finite sample performance of sequential designs for model identification
Optimal designs for dose finding studies
new test for the parametric form of the variance function in nonparametric regression
Robust designs for polynomial regression by maximizing a minimum of D- and D1-efficiencies
A comparative study of monotone nonparametric kernel estimates
A note on the Bickel-Rosenblatt test in autoregressive time series
Strictly monotone and smooth nonparametric regression for two or more variables
Canonical moments, orthogonal polynomials with application to statistics
On robust and efficient designs for risk estimation in epidemiologic studies
Strong approximation of eigenvalues of large dimensional Wishart matrices by roots of generalized Laguerre polynomials
Detecting deviations from stationarity
Detecting changes in the mean and variance of a time series : an approach based on U-statistics of triangular arrays
Finite sample performance of sequential designs for model identification
Optimal designs for dose finding studies
new test for the parametric form of the variance function in nonparametric regression
Robust designs for polynomial regression by maximizing a minimum of D- and D1-efficiencies
A comparative study of monotone nonparametric kernel estimates
A note on the Bickel-Rosenblatt test in autoregressive time series
Strictly monotone and smooth nonparametric regression for two or more variables
Canonical moments, orthogonal polynomials with application to statistics
On robust and efficient designs for risk estimation in epidemiologic studies
Strong approximation of eigenvalues of large dimensional Wishart matrices by roots of generalized Laguerre polynomials
Detecting deviations from stationarity
Detecting changes in the mean and variance of a time series : an approach based on U-statistics of triangular arrays
Finite sample performance of sequential designs for model identification
Optimal designs for dose finding studies
new test for the parametric form of the variance function in nonparametric regression
Robust designs for polynomial regression by maximizing a minimum of D- and D1-efficiencies
A comparative study of monotone nonparametric kernel estimates
A note on the Bickel-Rosenblatt test in autoregressive time series