plotPIP {LatentBMA}

Visualization of Posterior Inclusion Probabilities

Description

plotPIP produces a visualization of the posterior inclusion probabilities (PIPs) extracted from ULLGM_BMA results.

Usage

plotPIP(x,
        variable_names = NULL,
        sort           = TRUE)

Arguments

x

The output object of ULLGM_BMA.

variable_names

A character vector specifying the names of the columns of X.

sort

Logical, indicating whether the plot should be sorted by PIP. Defaults to TRUE.

Value

Returns a 'ggplot2::ggplot' object.

Author(s)

Gregor Zens

Examples

# Load package
library(LatentBMA)

# Example: Estimate a PLN model under a BRIC prior with m = p/2 using simulated data
# Note: Use more samples for actual analysis
# Note: nsave = 250 and nburn = 250 are for demonstration purposes
X <- matrix(rnorm(100*20), 100, 20)
z <- 2 + X %*% c(0.5, -0.5, rep(0, 18)) + rnorm(100, 0, sqrt(0.25))
y <- rpois(100, exp(z))
results_pln <- ULLGM_BMA(X = X, y = y, model = "PLN", nsave = 250, nburn = 250)
plotPIP(results_pln)