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Convert a normal (gaussian) distribution to a truncated normal distribution with specified minimum and maximum

Usage

norm2trunc(
  x,
  min = -Inf,
  max = Inf,
  mu = mean(x),
  sd = stats::sd(x),
  x_mu = mean(x),
  x_sd = stats::sd(x)
)

Arguments

x

the normally distributed vector

min

the minimum of the truncated distribution to return

max

the maximum of the truncated distribution to return

mu

the mean of the distribution to return (calculated from x if not given)

sd

the SD of the distribution to return (calculated from x if not given)

x_mu

the mean of x (calculated from x if not given)

x_sd

the SD of x (calculated from x if not given)

Value

a vector with a uniform distribution

Examples


x <- rnorm(10000)
y <- norm2trunc(x, 1, 7, 3.5, 2)
g <- ggplot2::ggplot() + ggplot2::geom_point(ggplot2::aes(x, y))
ggExtra::ggMarginal(g, type = "histogram")