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On asymptotically optimal confidence regions and tests for high-dimensional models
We propose a general method for constructing confidence intervals and statistical tests for single or low-dimensional components of a large parameter vector in a high-dimensional model. It can be… Expand
High-Dimensional Inference: Confidence Intervals, $p$-Values and R-Software hdi
We present a (selective) review of recent frequentist highdimensional inference methods for constructing p-values and confidence intervals in linear and generalized linear models. We include a… Expand
High-dimensional simultaneous inference with the bootstrap
We propose a residual and wild bootstrap methodology for individual and simultaneous inference in high-dimensional linear models with possibly non-Gaussian and heteroscedastic errors. We establish… Expand
Rejoinder on: High-dimensional simultaneous inference with the bootstrap
We thank the discussants for their interesting, inspiring and thoughtful comments and ideas. We provide here some responses.
Discussion on ‘regularized regression for categorical data (Tutz and Gertheiss)’
TG have written a masterpiece on modern regression with categorical covariables. Special attention is given to the case with ordinal categorical predictors: TG explain a variety of possibilities to… Expand