`gof_RPtest`

uses the `RPtest`

package to compute a goodness-of-fit test.

## Arguments

- x
A matrix of predictors.

- y
A vector of outcomes.

- m
Multiplier of null model sparsity.

- b
Additive increase to alternative sparsity.

## Details

First uses `cv.glmnet`

to select a model with `lambda.1se`

, then
tests the selected model against one with a value of `lambda`

chosen to increase the model sparsity.

## Examples

```
n <- 100
p <- 200
s0 <- 5
sim_data <- rXb(n, p, s0)
#> Error in rXb(n, p, s0): could not find function "rXb"
x <- sim_data$x
#> Error in eval(expr, envir, enclos): object 'sim_data' not found
beta <- sim_data$beta
#> Error in eval(expr, envir, enclos): object 'sim_data' not found
y <- x %*% beta + rnorm(n)
#> Error in eval(expr, envir, enclos): object 'x' not found
gof_RPtest(x, y)
#> Error in nrow(x): object 'x' not found
```