Zobrazeno 1 - 10
of 363
pro vyhledávání: '"Fried, Roland"'
Publikováno v:
Data Science in Science, 3(1), 2024
We study the problem of modeling and inference for spatio-temporal count processes. Our approach uses parsimonious parameterisations of multivariate autoregressive count time series models, including possible regression on covariates. We control the
Externí odkaz:
http://arxiv.org/abs/2404.02982
The occurrence of extreme events like heavy precipitation or storms at a certain location often shows a clustering behaviour and is thus not described well by a Poisson process. We construct a general model for the inter-exceedance times in between s
Externí odkaz:
http://arxiv.org/abs/2308.14625
Autor:
Pedeli, Xanthi, Fried, Roland
We study the problem of intervention effects generating various types of outliers in an integer-valued autoregressive model with Poisson innovations. We concentrate on outliers which enter the dynamics and can be seen as effects of extraordinary even
Externí odkaz:
http://arxiv.org/abs/2303.07933
We present a novel approach to test for heteroscedasticity of a non-stationary time series that is based on Gini's mean difference of logarithmic local sample variances. In order to analyse the large sample behaviour of our test statistic, we establi
Externí odkaz:
http://arxiv.org/abs/2002.10178
Population means and standard deviations are the most common estimands to quantify effects in factorial layouts. In fact, most statistical procedures in such designs are built towards inferring means or contrasts thereof. For more robust analyses, we
Externí odkaz:
http://arxiv.org/abs/1912.09146
Autor:
Gimbach, Sophie, Vogel, Daniel, Fried, Roland, Faraone, Stephen V., Banaschewski, Tobias, Buitelaar, Jan, Döpfner, Manfred, Ammer, Richard
Publikováno v:
In European Neuropsychopharmacology August 2023 73:24-35
Autor:
Dürre, Alexander, Fried, Roland
Classical moment based change point tests like the cusum test are very powerful in case of Gaussian time series with one change point but behave poorly under heavy tailed distributions and corrupted data. A new class of robust change point tests base
Externí odkaz:
http://arxiv.org/abs/1905.06201
Publikováno v:
In Journal of Multivariate Analysis March 2022 188
This paper considers the regional estimation of high quantiles of annual maximal river flow distributions $F$, an important problem from flood frequency analysis. Even though this particular problem has been addressed by many papers, less attention h
Externí odkaz:
http://arxiv.org/abs/1701.06455
Autor:
Dürre, Alexander, Fried, Roland
In panel data we observe a usually high number N of individuals over a time period T. Even if T is large one often assumes stability of the model over time. We propose a nonparametric and robust test for a change in location and derive its asymptotic
Externí odkaz:
http://arxiv.org/abs/1611.02571