Convert a uniform distribution to a normal (gaussian) distribution with specified mu and sd
Usage
unif2norm(x, mu = 0, sd = 1, min = NULL, max = NULL)
Arguments
- x
the uniformly distributed vector
- mu
the mean of the normal distribution to return
- sd
the SD of the normal distribution to return
- min
the minimum possible value of x (calculated from x if not given)
- max
the maximum possible value of x (calculated from x if not given)
Value
a vector with a gaussian distribution
Examples
x <- runif(10000)
y <- unif2norm(x)
#> min was not set, so guessed as 0.000105130549147725
#> max was not set, so guessed as 1.00002007436231
g <- ggplot2::ggplot() + ggplot2::geom_point(ggplot2::aes(x, y))
ggExtra::ggMarginal(g, type = "histogram")
