Plot for histogram density estimate

Plot for histogram density estimate for 1- and 2-dimensional data.

Usage

# S3 method for class 'histde'
plot(x, ...)

Arguments

x

object of class histde (output from histde)

...

other graphics parameters:

col: plotting colour for density estimate
col.fun: plotting colour function for levels
col.pt: plotting colour for data points
jitter: flag to jitter rug plot (1-d). Default is TRUE.
xlim,ylim: axes limits
xlab,ylab: axes labels
add: flag to add to current plot. Default is FALSE.
drawpoints: flag to draw data points on density estimate. Default is FALSE.
breaks: vector of break values of density estimate. Default is an nbreaks equilinear sequence over the data range.
nbreaks: number of breaks in breaks sequence
lty.rect,lwd.rect: line type/width for histogram box lines (2-d)
border: colour of histogram box lines (2-d)
col.rect: colour of histogram bars (1-d)
add.grid: flag to add histogram grid (2-d). Default is TRUE.

Value

Plots for 1-d and 2-d are sent to graphics window.

Details

For histde objects, the function headers for the different dimensional data are


  ## univariate
  plot(fhat, xlab, ylab="Density function", add=FALSE, drawpoints=FALSE,
     col.pt=4, jitter=FALSE, border=1, alpha=1, ...)

  ## bivariate
  plot(fhat, breaks, nbreaks=11, xlab, ylab, zlab="Density function", cex=1,
     pch=1, add=FALSE, drawpoints=FALSE, col, col.fun, alpha=1, col.pt=4,
     lty.rect=2, cex.text=1, border, lwd.rect=1, col.rect="transparent",
     add.grid=TRUE, ...)

The 1-d plot is a standard plot of a histogram generated by hist. If drawpoints=TRUE then a rug plot is added.

The 2-d plot is similar to the display="filled.contour" option from plot.kde with the default nbreaks=11 contour levels.

Examples

## univariate example
data(iris)
fhat <- histde(x=iris[,2])
plot(fhat, xlab="Sepal length")


## bivariate example
fhat <- histde(x=iris[,2:3])
plot(fhat, drawpoints=TRUE)
box()