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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 set to -7.75516334921122e-05
#> max was set to 1.00008334655538
g <- ggplot2::ggplot() + ggplot2::geom_point(ggplot2::aes(x, y))
ggExtra::ggMarginal(g, type = "histogram")