The `density()`

, `mean()`

, and `variance()`

methods are approximate as
they are based on numerical derivatives.

`dist_transformed(dist, transform, inverse)`

- 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.

```
# 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] 2.7500007 1.1672945 0.6931883 1.4901984 0.5363701 0.5053135 0.5833653
#> [8] 0.6704505 1.9811981 0.7642300
#>
```