Tools for transforming between N(0,1) variables and other distributions in predictor expressions

## Usage

```
bru_forward_transformation(qfun, x, ..., tail.split. = 0)
bru_inverse_transformation(pfun, x, ..., tail.split. = NULL)
```

## Arguments

- qfun
A quantile function object, such as

`qexp`

- x
Values to be transformed

- ...
Distribution parameters passed on to the

`qfun`

and`pfun`

functions- tail.split.
For x-values larger than

`tail.split.`

, upper quantile calculations are used internally, and for smaller values lower quantile calculations are used. This can avoid lack of accuracy in the distribution tails. If`NULL`

, forward calculations split at 0, and inverse calculations use lower tails only, potentially losing accuracy in the upper tails.- pfun
A CDF function object, such as

`pexp`

## Value

For

`bru_forward_transformation`

, a numeric vector

For

`bru_inverse_transformation`

, a numeric vector

## Examples

```
u <- rnorm(5, 0, 1)
y <- bru_forward_transformation(qexp, u, rate = 2)
v <- bru_inverse_transformation(pexp, y, rate = 2)
rbind(u, y, v)
#> [,1] [,2] [,3] [,4] [,5]
#> u 0.1990363 -2.0955269 1.062183 -0.4335553 -0.09024061
#> y 0.4324221 0.0091136 0.968706 0.2019624 0.31185534
#> v 0.1990363 -2.0955269 1.062183 -0.4335553 -0.09024061
```