Density plot with a normal curve

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",
  ...
)

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.

Value

Produces a plot. Returns nothing.

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

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

Author

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu

Examples

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