138 citations · 302 across the 32 of their papers we have counts for
3 papers · 1 filter
Scalable Estimation for Structured Additive Distributional Regression
Nikolaus Umlauf, Johannes Seiler, Mattias Wetscher +3
Recently, fitting probabilistic models have gained importance in many areas but estimation of such distributional models with very large data sets is a difficult task. In particula…
Assessment and adjustment of approximate inference algorithms using the law of total variance
Xuejun Yu, David J. Nott, Minh-Ngoc Tran +1
A common method for assessing validity of Bayesian sampling or approximate inference methods makes use of simulated data replicates for parameters drawn from the prior. Under conti…
bamlss: A Lego Toolbox for Flexible Bayesian Regression (and Beyond)
Nikolaus Umlauf, Nadja Klein, Thorsten Simon +1
Over the last decades, the challenges in applied regression and in predictive modeling have been changing considerably: (1) More flexible model specifications are needed as big(ger…