Scale-Dependent Hyperpriors in Structured Additive Distributional Regression
Marginal Density for Given Scale Parameter and Approximated Uniform Pr...
Marginal Density for Given Scale Parameter and Half-Normal Prior for $...
Marginal Density for Given Scale Parameter and Half-Cauchy Prior for $...
Marginal Density for Given Scale Parameter and Inverse Gamma Prior for...
Marginal Density for Given Scale Parameter and Scale-Dependent Prior f...
Compute Cumulative Distribution Function of Approximated (Differentiab...
Draw Random Numbers from Approximated (Differentiably) Uniform Distrib...
Prior precision matrix for spatial variable in Zambia data set
Malnutrition in Zambia
Compute Density Function of Approximated (Differentiably) Uniform Dist...
Computing Designmatrix for Splines
Find Scale Parameter for (Scale Dependent) Hyperprior
Find Scale Parameter for Hyperprior for Variances Where the Standard D...
Find Scale Parameter for Gamma (Half-Normal) Hyperprior
Find Scale Parameter for Generalised Beta Prime (Half-Cauchy) Hyperpri...
Find Scale Parameter for Inverse Gamma Hyperprior
Find Scale Parameter for Inverse Gamma Hyperprior of Linear Effects wi...
Find Scale Parameters for Inverse Gamma Hyperprior of Nonlinear Effect...
Find Scale Parameter for modular regression
Find Scale Parameter for Inverse Gamma Hyperprior of Linear Effects wi...
Marginal Density of
Utility functions for scale-dependent and alternative hyperpriors. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. Hyperpriors for all effects can be elicitated within the package. Including complex tensor product interaction terms and variable selection priors. The basic model is explained in in Klein and Kneib (2016) <doi:10.1214/15-BA983>.