Add an engine for grf quantile regression to rand_forest()

[topepo]

package site

This one is a little more complex than others since we use a special output type for the predicted values.

This can emulate the PR for the quantreg package: #1209

Notes on making a new engine at tidymodels.org

Checklist for adding a new engine

Engines may live in parsnip or an extension package.

• Write the initial functions that will populate the parsnip model “database”. For example, parsnip::set_fit() and so on. Suggested file name: {model_name}-data.R. [example]
• Engine-specific tuning parameters: Necessary parameter objects [example] should go into dials and the tunable() method [example] should go into parsnip. This needs a tibble which links engine arguments to dials parameter objects [example].
• Optionally create methods for translate() and check_args() to handle engine-specific cases. These .{model name} methods should go into parsnip, even if the engine is defined in an extension package, as they may contain code for various engines distributed across multiple extension packages. (example)
• Write unit tests for the engine-specific features.
• Write unit tests for model-specific features which require an engine. If parsnip does not contain any engines for the model, put these in the extension package.
• Write the engine-specific documentation. This documentation always goes into parsnip, regardless of where the engine is defined. See the README for the parsnip documentation system.
• If the engine is added in parsnip, update vignettes/articles/Examples.Rmd. If the engine is added in an extension package: does it have a corresponding article that needs updating? Does the README list available models/engines and needs updating?
• Add a documentation entry in NEWS.md.