ExtractPIPs function

Extract posterior inclusion probabilities (PIPs) from BKMR model fit

Extract posterior inclusion probabilities (PIPs) from BKMR model fit

Extract posterior inclusion probabilities (PIPs) from Bayesian Kernel Machine Regression (BKMR) model fit

ExtractPIPs(fit, sel = NULL, z.names = NULL)

Arguments

  • fit: An object containing the results returned by a the kmbayes function
  • sel: logical expression indicating samples to keep; defaults to keeping the second half of all samples
  • z.names: optional argument providing the names of the variables included in the h function.

Returns

a data frame with the variable-specific PIPs for BKMR fit with component-wise variable selection, and with the group-specific and conditional (within-group) PIPs for BKMR fit with hierarchical variable selection.

Details

For guided examples, go to https://jenfb.github.io/bkmr/overview.html

Examples

## First generate dataset set.seed(111) dat <- SimData(n = 50, M = 4) y <- dat$y Z <- dat$Z X <- dat$X ## Fit model with component-wise variable selection ## Using only 100 iterations to make example run quickly ## Typically should use a large number of iterations for inference set.seed(111) fitkm <- kmbayes(y = y, Z = Z, X = X, iter = 100, verbose = FALSE, varsel = TRUE) ExtractPIPs(fitkm)
  • Maintainer: Jennifer F. Bobb
  • License: GPL-2
  • Last published: 2022-03-28