Markus Kalisch
Markus Kalisch
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Zitiert von
Zitiert von
Estimating high-dimensional directed acyclic graphs with the PC-algorithm
M Kalisch, P Bühlmann
Journal of Machine Learning Research 8 (Mar), 613-636, 2007
Causal inference using graphical models with the R package pcalg
M Kalisch, M Mächler, D Colombo, MH Maathuis, P Bühlmann
Journal of Statistical Software 47 (11), 1-26, 2012
Estimating high-dimensional intervention effects from observational data
MH Maathuis, M Kalisch, P Bühlmann
The Annals of Statistics 37 (6A), 3133-3164, 2009
Learning high-dimensional directed acyclic graphs with latent and selection variables
D Colombo, MH Maathuis, M Kalisch, TS Richardson
The Annals of Statistics, 294-321, 2012
Predicting causal effects in large-scale systems from observational data
MH Maathuis, D Colombo, M Kalisch, P Bühlmann
Nature Methods 7 (4), 247-248, 2010
High-dimensional statistics with a view toward applications in biology
P Bühlmann, M Kalisch, L Meier
Annual Reviews, 2014
Selection of carbonic anhydrase IX inhibitors from one million DNA-encoded compounds
F Buller, M Steiner, K Frey, D Mircsof, J Scheuermann, M Kalisch, ...
ACS chemical biology 6 (4), 336-344, 2011
Variable selection in high-dimensional linear models: partially faithful distributions and the PC-simple algorithm
P Bühlmann, M Kalisch, MH Maathuis
Biometrika 97 (2), 261-278, 2010
Robustification of the PC-algorithm for directed acyclic graphs
M Kalisch, P Bühlmann
Journal of Computational and Graphical Statistics 17 (4), 773-789, 2008
The Penile Perception Score: an instrument enabling evaluation by surgeons and patient self-assessment after hypospadias repair
DM Weber, MA Landolt, R Gobet, M Kalisch, NK Greeff
The Journal of urology 189 (1), 189-193, 2013
Understanding human functioning using graphical models
M Kalisch, BAG Fellinghauer, E Grill, MH Maathuis, U Mansmann, ...
BMC Medical Research Methodology 10 (1), 14, 2010
A complete generalized adjustment criterion
E Perković, J Textor, M Kalisch, MH Maathuis
arXiv preprint arXiv:1507.01524, 2015
Robustified L2 boosting
RW Lutz, M Kalisch, P Bühlmann
Computational Statistics & Data Analysis 52 (7), 3331-3341, 2008
Causal structure learning and inference: a selective review
M Kalisch, P Bühlmann
Quality Technology & Quantitative Management 11 (1), 3-21, 2014
Complete graphical characterization and construction of adjustment sets in Markov equivalence classes of ancestral graphs
E Perkovic, J Textor, M Kalisch, MH Maathuis
The Journal of Machine Learning Research 18 (1), 8132-8193, 2017
Assessing statistical significance in multivariable genome wide association analysis
L Buzdugan, M Kalisch, A Navarro, D Schunk, E Fehr, P Bühlmann
Bioinformatics 32 (13), 1990-2000, 2016
Decomposition and model selection for large contingency tables
C Dahinden, M Kalisch, P Bühlmann
Biometrical Journal: Journal of Mathematical Methods in Biosciences 52 (2 …, 2010
Diode-pumped passively mode-locked Nd: YVO/sub 4/lasers with 40-GHz repetition rate
S Lecomte, M Kalisch, L Krainer, GJ Spuhler, R Paschotta, M Golling, ...
IEEE journal of quantum electronics 41 (1), 45-52, 2005
Interpreting and using CPDAGs with background knowledge
E Perković, M Kalisch, MH Maathuis
arXiv preprint arXiv:1707.02171, 2017
pcalg: Estimation of CPDAG/PAG and causal inference using the IDA algorithm
M Kalisch, M Mächler, D Colombo
UR L http://CRAN. R-project. org/package= pcalg. R package version, 1-1, 2010
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