README.md

In paasim/shinyproj: Interactive model selection using projpred

shinyproj

NOTE: THIS PACKAGE IS ARCHIVED AS IT DOES NOT (AND MAY NOT, AT LEAST IN THE NEAR FUTURE, BE UPDATED TO) SUPPORT THE CURRENT VERSION OF PROJPRED. PREVIOUS VERSIONS OF PROJPRED (E.G. 0.8) WILL STILL WORK.

An R package for interactive model selection using projpred.

Installation

shinyproj depends on the circlr-package, which can be installed from github. Other dependencies should be installed automatically from CRAN.

devtools::install_github('paasim/circlr')
devtools::install_github('paasim/shinyproj')

Usage

library(rstanarm)
library(projpred)
library(shinyproj)
options(mc.cores = parallel::detectCores())

# diabetes data set from http://web.stanford.edu/~hastie/Papers/LARS/
data('df_diabetes', package = 'shinyproj')

# sparsifying prior
n <- nrow(df_diabetes)
D <- ncol(df_diabetes) - 1
# prior guess for the number of relevant variables
p0 <- 3
# scale for tau (stan_glm will automatically scale this by sigma)
tau0 <- p0/(D-p0) * 1/sqrt(n)
prior_coeff <- hs(df = 1, global_df = 1, global_scale = tau0)

# fit the full model with rstanarm using the sparsifying prior
fit <- stan_glm(y ~ ., data = df_diabetes, prior = prior_coeff)

# perform the cross-validated variable selection
fit_cv <- cv_varsel(fit, nloo = n)

# explore the results
varsel_explore(fit_cv)

paasim/shinyproj documentation built on May 24, 2019, 5:56 p.m.