berryFunctions (version 1.17.0)

normPlot: Normal density plot

Description

Nice plot of normal density distribution

Usage

normPlot(mean = 0, sd = 1, width = 3, lines = TRUE, quant = TRUE,
  fill = addAlpha("blue", c(2:6, 7:2)/10), cumulative = TRUE, las = 1,
  main = paste("Normal density with\nmean =", signif(mean, 2), "and sd =",
  signif(sd, 2)), ylim = lim0(dnorm(mean, mean, sd)), ylab = "",
  xlab = "", type = "n", lty = 1, col = par("fg"), mar = c(2, 3, 3,
  3), keeppar = FALSE, ...)

Arguments

mean

average value as in dnorm. DEFAULT: 0

sd

standard deviation. DEFAULT: 1

width

distance (in sd) from plot ends to mean. DEFAULT: 3

lines

Should vertical lines be plotted at mean +- n*sd? DEFAULT: TRUE

quant

should quantile regions be drawn with fill colors? DEFAULT: TRUE

fill

color(s) passed to polygon. DEFAULT: addAlpha("blue",c(2:6,7:2)/10)

cumulative

Should cumulative density distribution be added? DEFAULT: TRUE

las

arguments passed to plot. DEFAULT: 1

main

main as in plot. DEFAULT: paste("Normal density with\nmean =", mean, "and sd =", sd)

ylim

limit for the y axis. DEFAULT: lim0(y)

ylab, xlab

labels for the axes. DEFAULT: ""

type, lty, col

arguments passed to lines. type="l" to add pdf line

mar

margins for plot passed to par. DEFAULT: c(2,3,3,3)

keeppar

should margin parameters be kept instead of being restored to previous value? DEFAULT: FALSE

…

further arguments passed to plot like lwd, xaxs, cex.axis, etc.

Value

None. Used for plotting.

Details

This function finds some nice defaults for very quickly plotting a normal distribution by just specifying mean and sd.

See Also

betaPlot, dnorm, https://cran.r-project.org/package=denstrip, https://cran.r-project.org/view=Distributions

Examples

# NOT RUN {
normPlot()
normPlot(81.7, 11.45)
normPlot(180, 11, quant=FALSE, width=2)

# }