Convert a normal (gaussian) distribution to a truncated normal distribution with specified minimum and maximum
norm2trunc(x, min = -Inf, max = Inf, mu = mean(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) |
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")
