plot.npnorm: Plotting a Nonparametric or Semiparametric Normal Mixture

Description

Function plot.npnorm plots the normal mixture.

Usage

# S3 method for npnorm
plot(
  x,
  mix,
  beta,
  breaks = NULL,
  col = 2,
  len = 100,
  add = FALSE,
  border.col = NULL,
  border.lwd = 1,
  fill = "lightgrey",
  main,
  lwd = 2,
  lty = 1,
  xlab = "Data",
  ylab = "Density",
  components = c("proportions", "curves", "null"),
  lty.components = 2,
  lwd.components = 2,
  ...
)

Arguments

x: an object of class npnorm.
mix: an object of class disc, for a discrete distribution.
beta: the structural parameter.
breaks: the rough number bins used for plotting the histogram.
col: the color of the density curve to be plotted.
len: the number of points roughly used to plot the density curve over the interval of length 8 times the component standard deviation around each component mean.
add: if FALSE, creates a new plot; if TRUE, adds the plot to the existing one.
border.col: color for the border of histogram boxes.
border.lwd: line width for the border of histogram boxes.
fill: color to fill in the histogram boxes.
main, lwd, lty, xlab, ylab: arguments for graphical parameters (see par).
components: if proportions (default), also show the support points and mixing proportions (in proportional vertical lines); if curves, also show the component density curves; if null, components are not shown.
lty.components, lwd.components: line type and width for the component curves.
...: arguments passed on to function plot.

Author

Yong Wang <yongwang@auckland.ac.nz>

References

Wang, Y. (2007). On fast computation of the non-parametric maximum likelihood estimate of a mixing distribution. Journal of the Royal Statistical Society, Ser. B, 69, 185-198.

Examples

Run this code


mix = disc(pt=c(0,4), pr=c(0.3,0.7))  # a discrete distribution
x = rnpnorm(200, mix, sd=1)
plot(x, mix, beta=1)