plot_mix_comps: Helper Function for Overlaying Mixture Components

In pdwaggoner/plotGMM: Tidy Tools for Visualizing Mixture Models

Helper Function for Overlaying Mixture Components

Description

Allows for plotting mixture components conditioned on a superimposed function meant for passage to ggplot's stat_function()

Usage

plot_mix_comps(x, mu = NULL, sigma = NULL, lam = 1, beta0 = NULL,
 beta1=NULL, alpha=NULL, beta=NULL,
 normal=FALSE, logisreg=FALSE,
 gamma=FALSE, poisson=FALSE)

Arguments

x	Input data
mu	Component mean
sigma	Component variance
lam	Component mixture weight
beta0	Coefficient values
beta1	Coefficient values
alpha	Initial shape parameters
beta	Initial parameter values
normal	Logical for normal distribution
logisreg	Logical for logistic regression mixtures
gamma	Logical for gamma distribution
poisson	Logical for poisson regression mixtures

Details

Allows for component curves to be superimposed over a mixture model plot

Examples

if(require(mixtools)){
mixmdl <- mixtools::normalmixEM(faithful$waiting, k = 2)
}
x <- mixmdl$x
x <- data.frame(x)
ggplot2::ggplot(data.frame(x)) +
  ggplot2::geom_density(ggplot2::aes(x), color="black", fill="black") +
  ggplot2::stat_function(geom = "line", fun = plot_mix_comps,
                args = list(mixmdl$mu[1], mixmdl$sigma[1], lam = mixmdl$lambda[1]),
                colour = "red") +
  ggplot2::stat_function(geom = "line", fun = plot_mix_comps,
                args = list(mixmdl$mu[2], mixmdl$sigma[2], lam = mixmdl$lambda[2]),
               colour = "blue")

pdwaggoner/plotGMM documentation built on Nov. 12, 2022, 4:35 a.m.