# Version 0.1.5

- Fixed NOTES in CRAN check
- Fixed plot.ranger()
- Fixed seq_unif.integer() so it will no longer duplicate unique values when length.out exceeds the number of unique values

# Version 0.1.4

- ClusterMF is hard deprecated. Replace any legacy call to ClusterMF with a call to MetaForest with the same arguments.
- Fixed PartialDependence for ranger objects
- Fixed bug where the argument “vi” was passed on to ranger()

# Version 0.1.3

- ClusterMF is soft deprecated; it has the same functionality as MetaForest. You can simply replace any call to ClusterMF with a call to MetaForest with the same arguments.
- A clustered MetaForest analysis no longer automatically doubles the number of trees estimated. Instead, it divides num.trees trees by two, rounding up to the nearest even number.
- Generic S3 methods are now properly declared as such, instead of being exported with their own documentation.
- Reduce dependencies by calculating partial dependence manually

# Version 0.1.2

- Rewrote WeightedScatter to jointly plot numeric and factor variables
- Rewrote PartialDependence to be an S3 generic, with methods for metaforest and rma models
- Rewrote PartialDependence to jointly plot numeric and factor variables
- Added ModelInfo_mf(), which returns a ModelInfo list for using metaforest with caret
- Added ModelInfo_rma(), which returns a ModelInfo list for using rma with caret

# Version 0.1.1

- Substantial update to PartialDependence
- PartialDependence now plots percentile interval for predictions
- PartialDependence now plots weighted raw data
- Improved speed of PartialDependence
- Improved speed of plot.MetaForest by vectorizing calculations
- Removed dependency on edarf
- Removed dependency on reshape2
- MetaForest and ClusterMF now return vi and weights vectors for plotting
- Improved speed of extract_proximity.MetaForest by using matrix operations
- Added WeightedScatter for weighted scatterplots of meta-analytic data