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rcompanion (version 2.4.30)

plotNormalDensity: Density plot with a normal curve

Description

Produces a density plot for a vector of values and adds a normal curve with the same mean and standard deviation. The plot can be used to quickly compare the distribution of data to a normal distribution.

Usage

plotNormalDensity(
  x,
  col1 = "white",
  col2 = "gray",
  col3 = "blue",
  border = NA,
  main = "",
  lwd = 2,
  length = 1000,
  adjust = 1,
  bw = "nrd0",
  kernel = "gaussian",
  ...
)

Value

Produces a plot. Returns nothing.

Arguments

x

A vector of values.

col1

The color of the density plot. Usually not visible.

col2

The color of the density polygon.

col3

The color of the normal line.

border

The color of the border around the density polygon.

main

The title displayed for the plot.

lwd

The width of the line in the plot.

length

The number of points in the line in the plot.

adjust

Passed to density. A lower value makes the density plot smoother.

bw

Passed to density.

kernel

Passed to density.

...

Other arguments passed to plot.

Author

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu

Details

The function plots a polygon based on the density function. The normal curve has the same mean and standard deviation as the values in the vector.

References

http://rcompanion.org/handbook/I_01.html

See Also

plotNormalHistogram, plotDensityHistogram

Examples

Run this code
### Plot of residuals from a model fit with lm
data(Catbus)
model = lm(Steps ~ Gender + Teacher,
           data = Catbus)
 plotNormalDensity(residuals(model))          

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