Zobrazeno 1 - 10
of 10
pro vyhledávání: '"FREMDT, STEFAN"'
Publikováno v:
Bernoulli 2015, Vol. 21, No. 2, 1238-1259
This paper is concerned with deriving the limit distributions of stopping times devised to sequentially uncover structural breaks in the parameters of an autoregressive moving average, ARMA, time series. The stopping rules are defined as the first ti
Externí odkaz:
http://arxiv.org/abs/1506.00859
Autor:
Fremdt, Stefan
In this paper the asymptotic distribution of the stopping time in Page's sequential cumulative sum (CUSUM) procedure is presented. Page as well as ordinary cumulative sums are considered as detectors for changes in the mean of observations satisfying
Externí odkaz:
http://arxiv.org/abs/1308.1241
Autor:
Fremdt, Stefan
In a variety of different settings cumulative sum (CUSUM) procedures have been applied for the sequential detection of structural breaks in the parameters of stochastic models. Yet their performance depends strongly on the time of change and is best
Externí odkaz:
http://arxiv.org/abs/1308.1237
Functional principal components (FPC's) provide the most important and most extensively used tool for dimension reduction and inference for functional data. The selection of the number, d, of the FPC's to be used in a specific procedure has attracted
Externí odkaz:
http://arxiv.org/abs/1302.6102
We propose a robust test for the equality of the covariance structures in two functional samples. The test statistic has a chi-square asymptotic distribution with a known number of degrees of freedom, which depends on the level of dimension reduction
Externí odkaz:
http://arxiv.org/abs/1104.4049
Publikováno v:
In Journal of Multivariate Analysis February 2014 124:313-332
Publikováno v:
Scandinavian Journal of Statistics, 2013 Mar 01. 40(1), 138-152.
Externí odkaz:
http://dx.doi.org/10.1111/j.1467-9469.2012.00796.x
Autor:
Fremdt, Stefan1 (AUTHOR) sfremdt@math.uni-koeln.de
Publikováno v:
Statistics. Feb2015, Vol. 49 Issue 1, p128-155. 28p.
Autor:
Fremdt, Stefan
This thesis is focussed on two areas of statistics, change-point analysis and functional data analysis, and the intersection of these two areas, i.e., the detection of structural breaks in functional stochastic models. The considered problems from (s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______199::caa433d357c154aae5bdf3ec39e802b7
https://kups.ub.uni-koeln.de/4967/
https://kups.ub.uni-koeln.de/4967/
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.