Gaussian Mixture plot in R

gmplot.r

library(ggplot2)

gg.mixEM <- function(EM) {
    require(ggplot2)
    x       <- with(EM,seq(min(x)-1,max(x)+1,len=1000))
    pars    <- with(EM,data.frame(comp=colnames(posterior), mu, sigma,lambda))
    em.df   <- data.frame(x=rep(x,each=nrow(pars)),pars)
    em.df$y <- with(em.df,lambda*dnorm(x,mean=mu,sd=sigma))
    ggplot(data.frame(x=EM$x),aes(x,y=..density..)) + 
        geom_histogram(fill=NA,color="black",bins=41)+
        geom_polygon(data=em.df,aes(x,y,fill=comp),color="grey50", alpha=0.5)+
        scale_fill_discrete("Component Means",labels=format(em.df$mu,digits=3))+
        theme_bw()+
        coord_cartesian(xlim = c(min(x)-1,max(x)),
                        expand = c(0,0))
}

# Examples
ores = mixtools::normalmixEM(resolution_time_second,
                             k = 2,
                             #mean.constr = NULL, 
                             #sd.constr = NULL,
                             #epsilon = 1e-15, 
                             #maxit = 1000,
                             #maxrestarts=50, 
                             #verb = TRUE, 
                             fast=FALSE, 
                             #ECM = FALSE,
                             #arbmean = TRUE, 
                             #arbvar = TRUE
                            )
                            
summary(ores)
gg.mixEM(ores)