Fabian Scheipl

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Helmut KüchenhoffInstitut für Statistik, LMU MünchenVerified email at stat.uni-muenchen.de
Sonja GrevenChair of Statistics, Humboldt-Universität zu BerlinVerified email at hu-berlin.de
Torsten HothornVerified email at R-project.org
Friedrich LeischInstitute of Statistics, University of Natural Resources and Life Sciences, Vienna, AustriaVerified email at boku.ac.at
Martin MächlerAdjunct Professor, ETH ZurichVerified email at stat.math.ethz.ch
Simon WoodStatistics, School of Mathematics, University of Edinburgh, UKVerified email at bath.edu
Steven C WalkerMcMaster UniversityVerified email at mcmaster.ca
Ana-Maria StaicuAssistant Professor, Statistics, North Carolina State UniversityVerified email at ncsu.edu
Jeff GoldsmithAssociate Professor, Department of Biostatistics, Columbia UniversityVerified email at columbia.edu
Andreas BenderLudwig-Maximilians-Universität MünchenVerified email at stat.uni-muenchen.de
Thomas KneibChair of Statistics, Georg-August-University GöttingenVerified email at uni-goettingen.de
Antonio GasparriniLondon School of Hygiene & Tropical MedicineVerified email at lshtm.ac.uk
Benjamin HofnerHead of Data Science and Methods, Paul-Ehrlich-InstituteVerified email at pei.de
Ciprian CrainiceanuProfessor of Biostatistics, Johns Hopkins UniversityVerified email at jhsph.edu
Philip ReissProfessor of Statistics, University of HaifaVerified email at stat.haifa.ac.il
Andrew G DayKingston Health Sciences Centre, Ontario CanadaVerified email at kingstonhsc.ca
Alice-Agnes GabrielAssociate Professor, Scripps Institution of Oceanography, UCSD; Guest Professor, LMU MunichVerified email at ucsd.edu
Jonathan GellarMathematica Policy ResearchVerified email at mathematica-mpr.com
Jan GertheissHelmut Schmidt UniversityVerified email at hsu-hh.de
Jaroslaw HarezlakProfessor at Indiana University School of Public Health-BloomingtonVerified email at iu.edu

Fabian Scheipl

LMU Munich / Munich Center for Machine Learning

Verified email at stat.uni-muenchen.de - Homepage

Statistics Bayesian Statistics Functional Data Analysis Additive Models Survival Analysis


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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	851	2008
gamm4: Generalized additive mixed models using mgcv and lme4. S Wood R Packag. version 0.2-3, 2014	762	2014
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	527	2009
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	370	2008
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	358	2014
Functional additive mixed models F Scheipl, AM Staicu, S Greven Journal of Computational and Graphical Statistics 24 (2), 477-501, 2015	278	2015
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, ...	272	2015
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	271	2016
mboost: Model-based boosting T Hothorn, P Buehlmann, T Kneib, M Schmid, B Hofner R package version 2, 9-1, 2012	252	2012
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	213	2010
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	209	2014
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	209	2009
Straightforward intermediate rank tensor product smoothing in mixed models SN Wood, F Scheipl, JJ Faraway Statistics and Computing 23, 341-360, 2013	205	2013
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	182	2014
A penalized framework for distributed lag non-linear models A Gasparrini, F Scheipl, B Armstrong, MG Kenward Biometrics 73 (3), 938-948, 2017	181	2017
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	170	2016
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	162	2012
Penalized function-on-function regression AE Ivanescu, AM Staicu, F Scheipl, S Greven Computational Statistics 30, 539-568, 2015	160	2015
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	138	2008
A general framework for functional regression modelling S Greven, F Scheipl Statistical Modelling 17 (1-2), 1-35, 2017	137	2017

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