Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Jens-Peter Kreiß"'
Publikováno v:
Journal of Time Series Analysis. 42:534-553
In this article, maximum deviations of sample autocovariances and autocorrelations from their theoretical counterparts over an increasing set of lags are considered. The asymptotic distribution of such statistics for physically dependent stationary t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8729adf418e3b7aa414ef30e158c7d23
https://doi.org/10.1111/jtsa.12604
https://doi.org/10.1111/jtsa.12604
Publikováno v:
Ann. Statist. 48, no. 4 (2020), 2404-2427
Existing frequency domain methods for bootstrapping time series have a limited range. Essentially, these procedures cover the case of linear time series with independent innovations, and some even require the time series to be Gaussian. In this paper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5eae7fad0c9cb0cc2a08321bc7138e33
https://projecteuclid.org/euclid.aos/1597370678
https://projecteuclid.org/euclid.aos/1597370678
Autor:
Jens-Peter Kreiß, Alexander Meister
Publikováno v:
Stochastic Processes and their Applications. 126:3009-3040
We consider extensions of the famous GARCH ( 1 , 1 ) model where the recursive equation for the volatilities is not specified by a parametric link but by a smooth autoregression function. Our goal is to estimate this function under nonparametric cons
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b966de9389777549daf2789b482966f2
https://doi.org/10.1016/j.spa.2016.03.010
https://doi.org/10.1016/j.spa.2016.03.010
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics. 22:151-159
Order selection of autoregressive processes is an active research topic in time series analysis, and the development and evaluation of automatic order selection criteria remains a challenging task for domain experts. We propose a visual analytics app
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7adf88fac8b63836ab57bf4612f44662
https://doi.org/10.1109/tvcg.2015.2467612
https://doi.org/10.1109/tvcg.2015.2467612
Fitting sparse models to high-dimensional time series is an important area of statistical inference. In this paper, we consider sparse vector autoregressive models and develop appropriate bootstrap methods to infer properties of such processes. Our b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e722df2b5b9a78ab5c184e1576794f14
Publikováno v:
Scandinavian Journal of Statistics. 42:1167-1193
We provide a consistent specification test for generalized autoregressive conditional heteroscedastic (GARCH (1,1)) models based on a test statistic of Cramer-von Mises type. Because the limit distribution of the test statistic under the null hypothe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::157f64c81276122ad4974a1f22ee39bb
https://doi.org/10.1111/sjos.12158
https://doi.org/10.1111/sjos.12158
Autor:
Jens-Peter Kreiss
Publikováno v:
Journal of Statistical Planning and Inference. 177:28-30
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b35451e4c673552fa75f318c5f584508
https://doi.org/10.1016/j.jspi.2015.10.012
https://doi.org/10.1016/j.jspi.2015.10.012
Publikováno v:
Bernoulli 23, no. 4B (2017), 2988-3020
The concept of the autoregressive (AR) sieve bootstrap is investigated for the case of spatial processes in $\mathbb{Z}^{2}$. This procedure fits AR models of increasing order to the given data and, via resampling of the residuals, generates bootstra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9444c8468f6a91392590045ea53ee2ba
https://doi.org/10.3150/16-bej835
https://doi.org/10.3150/16-bej835
Autor:
Marco Meyer, Jens-Peter Kreiss
Publikováno v:
Journal of Time Series Analysis. 36:377-397
The concept of autoregressive sieve bootstrap is investigated for the case of vector autoregressive (VAR) time series. This procedure fits a finite-order VAR model to the given data and generates residual-based bootstrap replicates of the time series
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2b01ea698fea37ce95166e61c1bafb3
https://doi.org/10.1111/jtsa.12090
https://doi.org/10.1111/jtsa.12090
Autor:
Thorsten Fink, Jens-Peter Kreiss
Publikováno v:
Journal of the Korean Statistical Society. 43:425-438
In this paper we consider autoregressive processes with random coefficients and develop bootstrap approaches that asymptotically work for the distribution of estimated autoregressive parameter as well as for the distribution of estimated variances of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::818a986654968ee0b82a694e1136961a
https://doi.org/10.1016/j.jkss.2014.01.001
https://doi.org/10.1016/j.jkss.2014.01.001