Version 0.1.5
- Better support for predefined tau2 values
 
- 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