Bayesian structured additive distributional regression for multivariate responses

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Bayesian Generalized Additive Models for Location, Scale, and Shape for Zero-Inflated and Overdispersed Count Data (2015, methodology): “A detailed analysis based on both count data regression for claim frequencies and zero adjusted models (as introduced in Heller, Stasinopoulos, and Rigby 2006) for claim sizes in the framework of GAMLSS is provided in Klein et al. (2014).”
Smoothing Parameter and Model Selection for General Smooth Models (2015, unknown): “dels falls into the general framework. 9 3.2 A special case: GAMLSS models The GAMLSS (or ‘distributional regression’) models discussed by Rigby and Stasinopoulos (2005) (and also Yee and Wild, 1996; Klein et al., 2014, 2015) fall within the scope of the general method. The idea is that we have inde”
Bayesian structured additive distributional regression with an application to regional income inequality in Germany (2015, methodology): “Similarly, multivariate extensions of beta regression lead to Dirichlet distributed responses representing multiple percentages that sum up to one; see Klein et al. (2015a) for a first attempt in this direction.”