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.
plotNormalDensity(x, col1 = "white", col2 = "gray", col3 = "blue",
border = NA, main = "", lwd = 2, length = 1000, adjust = 1,
bw = "nrd0", kernel = "gaussian", ...)
A vector of values.
The color of the density plot. Usually not visible.
The color of the density polygon.
The color of the normal line.
The color of the border around the density polygon.
The title displayed for the plot.
The width of the line in the plot.
The number of points in the line in the plot.
Passed to density
.
A lower value makes the density plot smoother.
Passed to density
.
Passed to density
.
Other arguments passed to plot
.
Produces a plot. Returns nothing.
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.
# NOT RUN {
### Plot of residuals from a model fit with lm
data(Catbus)
model = lm(Steps ~ Sex + Teacher,
data = Catbus)
plotNormalDensity(residuals(model))
# }
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