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Spike and Slab prior implementation for a Gaussian Location-Scale regression model

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Spike and Slab prior implementation for Gaussian Location-Scale Regression Models

I completed this project with two other students as part of the course advanced statistical programming with R at the University of Goettingen during the summer term 2021. It is an extension of a provided package for the couse.

Gaussian Location-Scale Regression Models

The Gaussian location-scale regression model is a multi-predictor model with explanatory variables for the mean (= location) and the standard deviation (= scale) of a response variable. This package implements maximum likelihood and Markov chain Monte Carlo (MCMC) inference, a parametric bootstrap algorithm, and diagnostic plots for the model.

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Spike and Slab prior implementation for a Gaussian Location-Scale regression model

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