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
Simon WoodStatistics, School of Mathematics, University of Edinburgh, UKVerified email at bath.edu
Ana-Maria StaicuAssistant Professor, Statistics, North Carolina State UniversityVerified email at ncsu.edu
Martin MächlerAdjunct Professor, ETH ZurichVerified email at stat.math.ethz.ch
Thomas KneibChair of Statistics, Georg-August-University GöttingenVerified email at uni-goettingen.de
Jeff GoldsmithAssociate Professor, Department of Biostatistics, Columbia UniversityVerified email at columbia.edu
Andreas BenderLudwig-Maximilians-Universität MünchenVerified email at stat.uni-muenchen.de
Benjamin HofnerHead of Data Science and Methods, Paul-Ehrlich-InstituteVerified email at pei.de
Steven C WalkerMcMaster UniversityVerified email at mcmaster.ca
Antonio GasparriniLondon School of Hygiene and Tropical MedicineVerified email at lshtm.ac.uk
Ciprian CrainiceanuProfessor of Biostatistics, Johns Hopkins UniversityVerified email at jhsph.edu
Philip ReissProfessor of Statistics, University of HaifaVerified email at stat.haifa.ac.il
Jonathan GellarMathematica Policy ResearchVerified email at mathematica-mpr.com
Andrew G DayKingston Health Sciences Centre, Ontario CanadaVerified email at kingstonhsc.ca
Jaroslaw HarezlakProfessor at Indiana University School of Public Health-BloomingtonVerified email at iu.edu
David RuppertAndrew Schultz Professor of Engineering, Professor of Statistics and Data Science, CornellVerified email at cornell.edu
Giles HookerProfessor of Statistics, University of PennsylvaniaVerified email at wharton.upenn.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	789	2008
gamm4: Generalized additive mixed models using mgcv and lme4 S Wood, F Scheipl R package version 0.2-3, 2014	566	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	488	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	346	2008
Package lme4: Linear mixed-effects models using Eigen and S4 D Bates, M Maechler, B Bolker, S Walker, RHB Christensen, H Singmann, ... CRAN Repos 1, 1-113, 2016	311	2016
mboost: Model-based boosting T Hothorn, P Bühlmann, T Kneib, M Schmid, B Hofner R package version 2, 9-1, 2012	306	2012
gamm4: Generalized Additive Mixed Models using ‘mgcv’and ‘lme4’. R package version 0.2-5 S Wood, F Scheipl	245	2017
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	228	2016
Functional additive mixed models F Scheipl, AM Staicu, S Greven Journal of Computational and Graphical Statistics 24 (2), 477-501, 2015	224	2015
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	197	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	185	2014
Straightforward intermediate rank tensor product smoothing in mixed models SN Wood, F Scheipl, JJ Faraway Statistics and Computing 23, 341-360, 2013	172	2013
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	172	2009
spikeSlabGAM: Bayesian variable selection, model choice and regularization for generalized additive mixed models in R F Scheipl arXiv preprint arXiv:1105.5253, 2011	152	2011
mvtnorm: Multivariate Normal and t Distributions. R package version 0.9-9991 A Genz, F Bretz, T Miwa, X Mi, F Leisch, F Scheipl, T Hothorn	151	2011
A penalized framework for distributed lag non‐linear models A Gasparrini, F Scheipl, B Armstrong, MG Kenward Biometrics 73 (3), 938-948, 2017	146	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	146	2016
Package ‘lme4’ D Bates, M Maechler, B Bolker, S Walker, RHB Christensen, H Singmann, ... URL http://lme4. r-forge. r-project. org, 2009	143	2009
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	136	2012
Penalized function-on-function regression AE Ivanescu, AM Staicu, F Scheipl, S Greven Computational Statistics 30, 539-568, 2015	135	2015

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