Generate a sequence of nquantiles, i.e., a sample of size n
with a nearperfect distribution.
distribution(type = "normal", ...) distribution_custom(n, type = "norm", ..., random = FALSE) distribution_beta(n, shape1, shape2, ncp = 0, random = FALSE, ...) distribution_binomial(n, size = 1, prob = 0.5, random = FALSE, ...) distribution_binom(n, size = 1, prob = 0.5, random = FALSE, ...) distribution_cauchy(n, location = 0, scale = 1, random = FALSE, ...) distribution_chisquared(n, df, ncp = 0, random = FALSE, ...) distribution_chisq(n, df, ncp = 0, random = FALSE, ...) distribution_gamma(n, shape, scale = 1, random = FALSE, ...) distribution_mixture_normal(n, mean = c(3, 3), sd = 1, random = FALSE, ...) distribution_normal(n, mean = 0, sd = 1, random = FALSE, ...) distribution_gaussian(n, mean = 0, sd = 1, random = FALSE, ...) distribution_poisson(n, lambda = 1, random = FALSE, ...) distribution_student(n, df, ncp, random = FALSE, ...) distribution_t(n, df, ncp, random = FALSE, ...) distribution_student_t(n, df, ncp, random = FALSE, ...) distribution_tweedie(n, xi = NULL, mu, phi, power = NULL, random = FALSE, ...) distribution_uniform(n, min = 0, max = 1, random = FALSE, ...) rnorm_perfect(n, mean = 0, sd = 1)
type  Can be any of the names from base R's Distributions, like 

...  Arguments passed to or from other methods. 
n  the number of observations 
random  Generate nearperfect or random (simple wrappers for the base R 
shape1  nonnegative parameters of the Beta distribution. 
shape2  nonnegative parameters of the Beta distribution. 
ncp  noncentrality parameter. 
size  number of trials (zero or more). 
prob  probability of success on each trial. 
location  location and scale parameters. 
scale  location and scale parameters. 
df  degrees of freedom (nonnegative, but can be noninteger). 
shape  shape and scale parameters. Must be positive,

mean  vector of means. 
sd  vector of standard deviations. 
lambda  vector of (nonnegative) means. 
xi  the value of \(\xi\) such that the variance is \(\mbox{var}[Y]=\phi\mu^{\xi}\) 
mu  the mean 
phi  the dispersion 
power  a synonym for \(\xi\) 
min  lower and upper limits of the distribution. Must be finite. 
max  lower and upper limits of the distribution. Must be finite. 