Modify a distribution with a transformation

The density(), mean(), and variance() methods are approximate as they are based on numerical derivatives.

dist_transformed(dist, transform, inverse)

Arguments

dist

A univariate distribution vector.

transform

A function used to transform the distribution. This transformation should be monotonic over appropriate domain.

inverse

The inverse of the transform function.

Examples

# Create a log normal distribution
dist <- dist_transformed(dist_normal(0, 0.5), exp, log)
density(dist, 1) # dlnorm(1, 0, 0.5)
#> [1] 0.7978846
cdf(dist, 4) # plnorm(4, 0, 0.5)
#> [1] 0.9972194
quantile(dist, 0.1) # qlnorm(0.1, 0, 0.5)
#> [1] 0.5268835
generate(dist, 10) # rlnorm(10, 0, 0.5)
#> [[1]]
#>  [1] 1.5076285 1.2335455 2.3533283 0.3302794 0.9117047 1.3987572 0.6719508
#>  [8] 0.4569739 1.8346730 2.1210368
#>