This function is deprecated in favor of `survival_reg()`

which uses the
`"censored regression"`

mode.

`surv_reg()`

defines a parametric survival model.

More information on how parsnip is used for modeling is at https://www.tidymodels.org/.

## Arguments

- mode
A single character string for the prediction outcome mode. The only possible value for this model is "regression".

- engine
A single character string specifying what computational engine to use for fitting.

- dist
A character string for the probability distribution of the outcome. The default is "weibull".

## Details

This function only defines what *type* of model is being fit. Once an engine
is specified, the *method* to fit the model is also defined. See
`set_engine()`

for more on setting the engine, including how to set engine
arguments.

The model is not trained or fit until the `fit()`

function is used
with the data.

Each of the arguments in this function other than `mode`

and `engine`

are
captured as quosures. To pass values
programmatically, use the injection operator like so:

```
value <- 1
surv_reg(argument = !!value)
```

Since survival models typically involve censoring (and require the use of
`survival::Surv()`

objects), the `fit.model_spec()`

function will require that the
survival model be specified via the formula interface.