Plot iNUDGE Mixture Component Function

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Description

Plot each estimated individual components of iNUDGE mixture model fitted using inudge.fit.

Usage

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inudge.plot.mix(obj, amplify = 1, resolution = 100, new.plot = TRUE, ...)

Arguments

obj

a list object returned by inudge.fit function.

amplify

optional scaling factor for visualization purposes.

resolution

optional bandwidth used to estimate the density function. Higher number makes a smoother curve.

new.plot

optional logical variable on whether to create new plot.

...

additional graphical arguments to be passed to methods (see par).

See Also

inudge.plot.comp, inudge.plot.fit, inudge.plot.qq, DIME.plot.fit, gng.plot.fit.

Examples

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library(DIME)

# generate simulated datasets with underlying uniform and 2-normal distributions
set.seed(1234);
N1 <- 1500; N2 <- 500; rmu <- c(-2.25,1.5); rsigma <- c(1,1); 
rpi <- c(.10,.45,.45); a <- (-6); b <- 6; 
chr4 <- list(c(-runif(ceiling(rpi[1]*N1),min = a,max =b),
  rnorm(ceiling(rpi[2]*N1),rmu[1],rsigma[1]), 
  rnorm(ceiling(rpi[3]*N1),rmu[2],rsigma[2])));
chr9 <- list(c(-runif(ceiling(rpi[1]*N2),min = a,max =b),
  rnorm(ceiling(rpi[2]*N2),rmu[1],rsigma[1]), 
  rnorm(ceiling(rpi[3]*N2),rmu[2],rsigma[2])));
# analyzing chromosome 4 and 9
data <- list(chr4,chr9);

# fit iNUDGE model
set.seed(1234);
bestInudge <- inudge.fit(data, K = 2, max.iter=20);

# plot estimated iNUDGE model imposed on the histogram of observed data
hist(unlist(data),freq=FALSE,breaks=40);
inudge.plot.mix(bestInudge,resolution=1000,new.plot=FALSE,col="red");