Zobrazeno 1 - 10
of 262
pro vyhledávání: '"Stergios B"'
Publikováno v:
Frontiers in Environmental Science, Vol 6 (2018)
An understanding of low frequency climatic variations is important for climatologists and planning by the public for informed climate mitigation and adaptation. This study applies recent advances in statistical change-point methodology to the variabi
Externí odkaz:
https://doaj.org/article/963c77bf979d4590b035ab27aabf7261
We study a plug in least squares estimator for the change point parameter where change is in the mean of a high dimensional random vector under subgaussian or subexponential distributions. We obtain sufficient conditions under which this estimator po
Externí odkaz:
http://arxiv.org/abs/2007.01888
We develop a projected least squares estimator for the change point parameter in a high dimensional time series model with a potential change point. Importantly we work under the setup where the jump size may be near the boundary of the region of det
Externí odkaz:
http://arxiv.org/abs/1909.08101
Binary segmentation, which is sequential in nature is thus far the most widely used method for identifying multiple change points in statistical models. Here we propose a top down methodology called arbitrary segmentation that proceeds in a conceptua
Externí odkaz:
http://arxiv.org/abs/1906.04396
Publikováno v:
In International Journal of Production Economics March 2023 257
Autor:
Fotopoulos, Stergios B.1 (AUTHOR) fotopo@wsu.edu, Kaul, Abhishek2 (AUTHOR), Pavlopoulos, Vasileios3 (AUTHOR), Jandhyala, Venkata K.2 (AUTHOR)
Publikováno v:
Statistical Papers. Jul2024, Vol. 65 Issue 5, p2887-2913. 27p.
We propose a two step algorithm based on $\ell_1/\ell_0$ regularization for the detection and estimation of parameters of a high dimensional change point regression model and provide the corresponding rates of convergence for the change point as well
Externí odkaz:
http://arxiv.org/abs/1805.03719
Autor:
Fotopoulos, Stergios B.
Publikováno v:
Statistical Inference for Stochastic Processes; Jul2024, Vol. 27 Issue 2, p335-372, 38p
The purpose of this study is to provide a new methodology of how one can consistently estimate a change-point in time series data. In contrast with previous studies, the suggested methodology employs only the empirical spectral density and its first
Externí odkaz:
http://arxiv.org/abs/1611.06381
Publikováno v:
Annals of Applied Statistics 2010, Vol. 4, No. 2, 1081-1104
We derive exact computable expressions for the asymptotic distribution of the change-point mle when a change in the mean occurred at an unknown point of a sequence of time-ordered independent Gaussian random variables. The derivation, which assumes t
Externí odkaz:
http://arxiv.org/abs/1011.2322