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R code and BayesX scripts for effect selection and complexity reduction on basis of the Normal Beta Prime Spike and Slab Prior

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Applications appearing in our Bayesian Effect Selection paper

All results where obtained via BayesX.

  1. Housing Prices
  2. Nigeria Undernutrition
  3. Patent Data
  4. Simulated Recomposed Effect Samples

Effect Selection in hierarchical location-scale model with spatial heterogeneity
Data is not available publicly, unfortunately.

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Effect Selection for predictors of all parameters (mu1, mu2, sigma1, sigma2, rho) in bivariate Gaussian location-scale model of undernutrition scores
Data is not available publicly, unfortunately.

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Effect Selection for predictors of lambda and pi in zero-inflated Poisson model on patent citation data. Calculates various (proper) scores for 10-Fold CV. Data is available.


Simulates data for effect selection in simple Gaussian mean model and plots recomposed effect estimates on basis of linear samples and samples of nonlinear deviations.

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R code and BayesX scripts for effect selection and complexity reduction on basis of the Normal Beta Prime Spike and Slab Prior

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