Rerf

* Updated tests to accomodate the new `sample()` algorithm in R 3.5.3

* The `PrintTree` function has been added to aid in viewing the
cut-points, features, and other statistics in a particular tree of a
forest.

* Urerf now supports using the Bayesian information criterion (BIC) from
the `mclust` package for determining the best split.

* Feature importance calculations now correctly handle features whose
weight vectors parametrize the same line. Also, when the projection
weights are continuous we tabulate how many times a unique combination
of features was used, ignoring the weights.

* An issue where the `split.cpp` function split the data `A` into `{A, {}}`
has been resolved by computing equivalence within some factor of
machine precision instead of exactly.

* The option `rho` in the RerF function has been re-named to `sparsity` to match with the algorithm explanation.

* The default parameters sent to the RandMat\* functions now properly account for categorical columns.

* The defualts have changed for the following parameters:
* `min.parent = 1`
* `max.depth = 0`
* `stratify = TRUE`

* Predictions are made based on the average of posteriors rather than average of the predictions.

* The included RandMat\* functions have been re-structured for ease of use with their own examples and documentation. This should make it easier to create and include a user defined function to use as an input option.

* We are now using `testthat` for all of our function tests moving forward.

* Housekeeping: Updated the README and changed maintainers.