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stat.ME2024★ 2 cited
Errors-In-Variables Model Fitting for Partially Unpaired Data Utilizing Mixture Models
Wolfgang Hoegele, Sarah Brockhaus
We introduce a general framework for regression in the errors-in-variables regime, allowing for full flexibility about the dimensionality of the data, observational error probabili…
stat.ME2018
Boosting Functional Response Models for Location, Scale and Shape with an Application to Bacterial Competition
Almond Stöcker, Sarah Brockhaus, Sophia Schaffer +3
We extend Generalized Additive Models for Location, Scale, and Shape (GAMLSS) to regression with functional response. This allows us to simultaneously model point-wise mean curves,…