bayespcaSim

Simulation Study for the Bayes PCA method

The method (Bayes PCA) is compared with the sparse PCA specification of the model. Simulations are run with the R (>= 3.3.0) programming language. Bayesian PCA is implemented via the bayespca package by D. Vidotto (https://github.com/davidevdt/bayespca), while Sparse PCA is implemented with the elasticnet package by H. Zou (https://github.com/cran/elasticnet).

Run the simulations

To run the simulations:

1. Install the required R packages:
   • devtools::install_github("cran/elasticnet")
   • devtools::install_github("davidevdt/bayespca")
2. Launch main.R ; in this file, simulation parameters and plotting functions can be specified
   • modify the simulation parameters by changing the values that appear before runSim()
   • select the type of results you want to visualize: plotN = 1 for Tucker congruence, plotN = 2 for proportion of correct zeros/nonzeros, plotN = 3 for the reconstruction errors