Generate a sample of size n with a near-perfect distribution.

rnorm_perfect(n, mean = 0, sd = 1)

rcauchy_perfect(n, location = 0, scale = 1)

rpois_perfect(n, lambda)

rt_perfect(n, df, ncp)

## Arguments

n number of observations. If length(n) > 1, the length is taken to be the number required. vector of means. vector of standard deviations. location and scale parameters. location and scale parameters. vector of (non-negative) means. degrees of freedom ($$> 0$$, maybe non-integer). df = Inf is allowed. non-centrality parameter $$\delta$$; currently except for rt(), only for abs(ncp) <= 37.62. If omitted, use the central t distribution.

## Examples

library(bayestestR)
x <- rnorm_perfect(n = 10)
plot(density(x))