ENMeval 0.3.0
===========
o  Changed the default behavior to use the 'maxnet' function of the 'maxnet' package instead of the 'maxent.jar' program, and removed the dependency on the 'rJava' package by default, among others.
o  Added an algorithm slot to the ENMevaluation object.
o  Added information on the aggregation factor(s) or number of k folds to the ENMevaluation object when relevant.
o  Corrected use of 'corrected.var' in the 'tuning' function.
o  Changed some column names in the @results table to be more intuitive and compatable with the R package, Wallace.


ENMeval 0.2.2
===========
o  Added a vignette. Type: vignette('ENMeval-vignette', package='ENMeval')
o  Added an option to pass additional arguments to maxent (e.g., prevalence)
o  Added a function to extract variable importance for maxent models
o  Fixed an inconsistency with the AICc columns of the results table when rasterPreds=F
o  Fixed potential errors in the partitioning methods functions when used independently
o  Added some progress bar options to increase compatibility with Wallace


ENMeval 0.2.1
===========
o  Fixed an error in the organization of results table when bin.output=T


ENMeval 0.2.0
===========
o  Fixed a bug that allowed only a single categorical variable; now multiple categorical variables work.
o  Added an option to run the tuning function in parallel.
o  Added a slot in ENMevaluation object class to hold Maxent model objects.  This allows the user to access the lambda values and original results table generated by Maxent.
o  Added arguments in ENMevaluate function to turn off raster prediction generation to save time.


ENMeval 0.1.1
===========
o  This version corrects the calc.aicc function that, in version 0.1.0, could give erroneous results when used with multiple models simultaneously.  AICc, delta.AICc, and w.AIC values calculated in v.0.1.0 are potentially flawed!


ENMeval 0.1.0
===========
o  This is the initial version of ENMeval.  The main function is ENMeval::ENMevaluate().
