23 citations · 53 across the 7 of their papers we have counts for
7 papers
permApprox: a general framework for accurate permutation p-value approximation
Stefanie Peschel, Anne-Laure Boulesteix, Erika von Mutius +1
Permutation procedures are common practice in hypothesis testing when distributional assumptions about the test statistic are not met or unknown. With only few permutations, empiri…
Factorized Structured Regression for Large-Scale Varying Coefficient Models
David Rügamer, Andreas Bender, Simon Wiegrebe +4
Recommender Systems (RS) pervade many aspects of our everyday digital life. Proposed to work at scale, state-of-the-art RS allow the modeling of thousands of interactions and facil…
latentcor: An R Package for estimating latent correlations from mixed data types
Mingze Huang, Christian L. Müller, Irina Gaynanova
We present `latentcor`, an R package for correlation estimation from data with mixed variable types. Mixed variables types, including continuous, binary, ordinal, zero-inflated, or…
c-lasso -- a Python package for constrained sparse and robust regression and classification
Léo Simpson, Patrick L. Combettes, Christian L. Müller
We introduce c-lasso, a Python package that enables sparse and robust linear regression and classification with linear equality constraints. The underlying statistical forward mode…
Fast computation of latent correlations
Grace Yoon, Christian L. Müller, Irina Gaynanova
Latent Gaussian copula models provide a powerful means to perform multi-view data integration since these models can seamlessly express dependencies between mixed variable types (b…
Perspective Maximum Likelihood-Type Estimation via Proximal Decomposition
Patrick L. Combettes, Christian L. Müller
We introduce an optimization model for maximum likelihood-type estimation (M-estimation) that generalizes a large class of existing statistical models, including Huber's concomitan…
Generalized Stability Approach for Regularized Graphical Models
Christian L. Müller, Richard Bonneau, Zachary Kurtz
Selecting regularization parameters in penalized high-dimensional graphical models in a principled, data-driven, and computationally efficient manner continues to be one of the key…