distribution.plot: Create a four-panel distribution plot
In Auburngrads/SMRD: Statistical Methods For Reliability Data

Create a four-panel distribution plot

distribution.plot(
  distribution,
  shape,
  prob.range = c(0.01, 0.99),
  number.points = 1000,
  scale = rep(1, length(shape)),
  location = rep(0, length(shape)),
  shape2 = 1,
  exponential2 = T,
  cex = 16,
  lwd = 1.5,
  ...
)

`distribution`	Generates an array of ggplot2 grobs showing the cdf, pdf, survival function and hazard function for a distribution
`shape`	A vector of shape parameters
`prob.range`	A vector (length 2) of values between 0 and 1 providing the lower and upper limits of the probability range
`number.points`	The number points to be used in the plot
`scale`	A numeric value of the scale parameter (see Details)
`location`	A numeric value of the location parameter (see Details)
`shape2`	A numeric value of the second shape parameter (see Details)
`exponential2`	Is this 2-param exponential
`cex`	A positive numeric value giving the amount by which the plot text should be magnified relative to the default.
`lwd`	A positive numeric value giving the amount by which the line widths should be magnified relative to the default.
`...`	Currently not used

## Not run: 
distribution.plot("Exponential",
                  shape = c(.5,1))

distribution.plot("Lognormal",
                  shape = c(.3, .8))

distribution.plot("Normal",
                  shape = c( .30, .5,.8),
                  location = 5)

distribution.plot("Weibull",
                  shape = c(.8,1,1.5))

distribution.plot("Smallest Extreme Value",
                  shape = c(5,6,7),
                  location = 50)

distribution.plot("Largest Extreme Value",
                  shape = c(5, 6, 7),
                  location = 10)

distribution.plot("Logistic",
                  shape = c(1, 2, 3),
                  location = 15)

distribution.plot("Loglogistic",
                  shape = c(.2,.4,.6), 
                  prob.range = c(0.001, 0.95))

## End(Not run)