Zobrazeno 1 - 10
of 30
pro vyhledávání: '"A. B�hlmann"'
Autor:
Renaux, Claude, B��hlmann, Peter
Hierarchical inference in (generalized) regression problems is powerful for finding significant groups or even single covariates, especially in high-dimensional settings where identifiability of the entire regression parameter vector may be ill-posed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82ece49720c9c21dfc2b4383ed65559d
http://arxiv.org/abs/2104.15028
http://arxiv.org/abs/2104.15028
We consider estimation of undirected Gaussian graphical models and inverse covariances in high-dimensional scenarios by penalizing the corresponding precision matrix. While single $L_1$ (Graphical Lasso) and $L_2$ (Graphical Ridge) penalties for the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::043a6a74adf7e584535f3bd31b47f1bd
http://arxiv.org/abs/2101.02148
http://arxiv.org/abs/2101.02148
Publikováno v:
Electronic Journal of Statistics, 15 (2)
High-dimensional group inference is an essential part of statistical methods for analysing complex data sets, including hierarchical testing, tests of interaction, detection of heterogeneous treatment effects and inference for local heritability. Gro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ea7f0d9162cdb76917a935a2c736a0e
https://hdl.handle.net/20.500.11850/525120
https://hdl.handle.net/20.500.11850/525120
Autor:
B��hlmann, Peter, ��evid, Domagoj
We review some recent work on removing hidden confounding and causal regularization from a unified viewpoint. We describe how simple and user-friendly techniques improve stability, replicability and distributional robustness in heterogeneous data. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95f3ee45f3dfad13999d6ef0def8ff3b
http://arxiv.org/abs/2008.06234
http://arxiv.org/abs/2008.06234
We propose a family of tests to assess the goodness-of-fit of a high-dimensional generalized linear model. Our framework is flexible and may be used to construct an omnibus test or directed against testing specific non-linearities and interaction eff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::52e66898de0be810691cd400f06ddf8c
http://arxiv.org/abs/1908.03606
http://arxiv.org/abs/1908.03606
We propose estimation methods for change points in high-dimensional covariance structures with an emphasis on challenging scenarios with missing values. We advocate three imputation like methods and investigate their implications on common losses use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::acf39821bdf0d47664a718ba3531925e
http://arxiv.org/abs/1907.05409
http://arxiv.org/abs/1907.05409
We consider the problem of predicting a response variable from a set of covariates on a data set that differs in distribution from the training data. Causal parameters are optimal in terms of predictive accuracy if in the new distribution either many
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5e21b9af514e6ba5fae58ddce1c263a
http://arxiv.org/abs/1801.06229
http://arxiv.org/abs/1801.06229
Autor:
Esquinazi, Pablo D., Precker, Christian E., Stiller, Markus, Cordeiro, Tiago R. S., Barzola-Quiquia, Jose, Setzer, Annette, B��hlmann, Winfried
In the last 43 years several hints were reported suggesting the existence of granular superconductivity above room temperature in different graphite-based systems. In this paper some of the results are reviewed, giving special attention to those obta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a364c5bc6f64fff1f6da64faec44659f
http://arxiv.org/abs/1709.00259
http://arxiv.org/abs/1709.00259
Autor:
Precker, Christian E., Esquinazi, Pablo D., Champi, Ana, Barzola-Quiquia, Jos��, Zoraghi, Mahsa, Mui��os-Landin, Santiago, Setzer, Annette, B��hlmann, Winfried, Spemann, Daniel, Meijer, Jan, Muenster, Tom, Baehre, Oliver, Kloess, Gert, Beth, Henning
Publikováno v:
New Journal of Physics
New J. Phys. 18 (2016) 113041 doi:10.1088/1367-2630/18/11/113041
New J. Phys. 18 (2016) 113041 doi:10.1088/1367-2630/18/11/113041
Measuring with high precision the electrical resistance of highly ordered natural graphite samples from a Brazil mine, we have identified a transition at $\sim$350~K with $\sim$40~K transition width. The step-like change in temperature of the resista
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee066d1a915a00a8c120621a9feb62c0
https://hdl.handle.net/21.11116/0000-0002-F207-521.11116/0000-0002-F209-3
https://hdl.handle.net/21.11116/0000-0002-F207-521.11116/0000-0002-F209-3