4 papers
Efficient Computation of Sparse and Robust Maximum Association Estimators
Pia Pfeiffer, Andreas Alfons, Peter Filzmoser
Robust statistical estimators offer resilience against outliers but are often computationally challenging, particularly in high-dimensional sparse settings. Modern optimization tec…
spar: Sparse Projected Averaged Regression in R
Roman Parzer, Laura Vana-Gür, Peter Filzmoser
Package spar for R builds ensembles of predictive generalized linear models with high-dimensional predictors. It employs an algorithm utilizing variable screening and random projec…
Data-Driven Random Projection and Screening for High-Dimensional Generalized Linear Models
Roman Parzer, Peter Filzmoser, Laura Vana-Gür
We address the challenge of correlated predictors in high-dimensional GLMs, where regression coefficients range from sparse to dense, by proposing a data-driven random projection m…
Cellwise robust and sparse principal component analysis
Pia Pfeiffer, Laura Vana-Gür, Peter Filzmoser
A first proposal of a sparse and cellwise robust PCA method is presented. Robustness to single outlying cells in the data matrix is achieved by substituting the squared loss functi…