How to plot the log likelihood associated with each iteration of EM algorithm and the density of each component?

Question

I am new to R. I am working with mixture model and would like to get the plot the of the log likelihood associated with each iteration of the EM algorithm and the density of each component. I would like to do that manually.

Any help please?

Answer 1

I'm assuming you are able to calculate the log-likelihood and density in each iteration of your EM algorithm.

The general way to plot a function in R (of which a log-likelihood and density are) is to (a) create inputs for the function over the domain your interested in, (b) generate outputs from your function and save in a data frame, then (c) plot the function using the data frame. Here's an example of plotting a mixture model density using the 2D mixture model given by:

library(mvtnorm)
# example 2D mixture density
mixture_model_density <- function(x){
  a <- 0.3
  a * dmvnorm(x = x, mean = c(3, 2)) + (1 - a) * dmvnorm(x = x, mean = c(2.5,5.5))
}

(a) Create inputs:

grid_space <- 0.2
x <- seq(from = 0, to = 10, by = grid_space)
y <- seq(from = 0, to = 10, by = grid_space)
grid_mat <- expand.grid(x=x,y=y)

(b) Generate outputs:

 grid_mat$mm_dens <- mixture_model_density(grid_mat)

(c) Plot results:

ggplot(grid_mat) + stat_contour(aes(x = x, y = y, z = mm_dens))