1 citations · 1 across the 2 of their papers we have counts for
4 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…
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…
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…