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Fabian Scheipl
Fabian Scheipl
LMU Munich / Munich Center for Machine Learning
Verified email at stat.uni-muenchen.de - Homepage
Title
Cited by
Cited by
Year
mvtnorm: Multivariate Normal and t Distributions
A Genz, F Bretz, T Miwa, X Mi, F Leisch, F Scheipl, T Hothorn
R package version 0.9-2, URL http://CRAN. R-project. org/package= mvtnorm, 2008
8512008
gamm4: Generalized additive mixed models using mgcv and lme4.
S Wood
R Packag. version 0.2-3, 2014
7642014
Predictors of severe systemic anaphylactic reactions in patients with Hymenoptera venom allergy: importance of baseline serum tryptase—a study of the European Academy of …
F Ruëff, B Przybilla, MB Biló, U Müller, F Scheipl, W Aberer, J Birnbaum, ...
Journal of Allergy and Clinical Immunology 124 (5), 1047-1054, 2009
5272009
Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models
F Scheipl, S Greven, H Küchenhoff
Computational statistics & data analysis 52 (7), 3283-3299, 2008
3712008
Package lme4: Linear mixed-effects models using Eigen and S4
D Bates, M Maechler, B Bolker, S Walker, RHB Christensen, H Singmann, ...
R package version 67, 2014
3622014
Functional additive mixed models
F Scheipl, AM Staicu, S Greven
Journal of Computational and Graphical Statistics 24 (2), 477-501, 2015
2792015
lme4: Linear mixed-effects models using Eigen and S4. R package version 1.1–7. 2014
D Bates, M Mächler, B Bolker, S Walker, RHB Christensen, H Singmann, ...
2732015
Thrombus histology suggests cardioembolic cause in cryptogenic stroke
T Boeckh-Behrens, JF Kleine, C Zimmer, F Neff, F Scheipl, J Pelisek, ...
Stroke 47 (7), 1864-1871, 2016
2692016
mboost: Model-based boosting
T Hothorn, P Buehlmann, T Kneib, M Schmid, B Hofner
R package version 2, 9-1, 2012
2522012
Predictors of side effects during the buildup phase of venom immunotherapy for Hymenoptera venom allergy: the importance of baseline serum tryptase
F Ruëff, B Przybilla, MB Biló, U Müller, F Scheipl, W Aberer, J Birnbaum, ...
Journal of Allergy and Clinical Immunology 126 (1), 105-111. e5, 2010
2132010
Functional generalized additive models
MW McLean, G Hooker, AM Staicu, F Scheipl, D Ruppert
Journal of Computational and Graphical Statistics 23 (1), 249-269, 2014
2122014
Fear-related behaviour of dogs in veterinary practice
D Döring, A Roscher, F Scheipl, H Küchenhoff, MH Erhard
The Veterinary Journal 182 (1), 38-43, 2009
2102009
Straightforward intermediate rank tensor product smoothing in mixed models
SN Wood, F Scheipl, JJ Faraway
Statistics and Computing 23, 341-360, 2013
2052013
A penalized framework for distributed lag non-linear models
A Gasparrini, F Scheipl, B Armstrong, MG Kenward
Biometrics 73 (3), 938-948, 2017
1832017
Refund: Regression with functional data
J Goldsmith, F Scheipl, L Huang, J Wrobel, J Gellar, J Harezlak, ...
R package version 0.1-16 572, 2016
1702016
Penalized function-on-function regression
AE Ivanescu, AM Staicu, F Scheipl, S Greven
Computational Statistics 30, 539-568, 2015
1622015
Linear mixed-effect models using Eigen and S4
D Bates, M Maechler, B Bolker, S Walker, RHB Christensen, H Singmann, ...
R package version 1, 2014
1612014
Spike-and-Slab Priors for Function Selection in Structured Additive Regression Models
F Scheipl, L Fahrmeir, T Kneib
Journal of the American Statistical Association 107 (500), 1518-1532, 2012
1612012
A general framework for functional regression modelling
S Greven, F Scheipl
Statistical Modelling 17 (1-2), 1-35, 2017
1382017
Mvtnorm: multivariate normal and t distributions. R package version 0.9-2
A Genz, F Bretz, T Miwa, X Mi, F Leisch, F Scheipl, T Hothorn
1382008
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Articles 1–20