# datafsm 0.2.2

* Rewrote covariate testing in `fitnessCPP` to fix memory access errors.
* Added new vignette, giving an example using real data from Fudenberg,
  Rand, and Dreber.
* Change progress reports to use `message()` and `warning()` instead of 
  `print()` and `cat()`
* Added new dataset with iterated prisoner's dilemma games from Nay and 
  Vorobeychik (2016).

# datafsm 0.2.1

* Updated tests to work with forthcoming testthat version 2.0.0

# datafsm 0.2.0

* Updated to use new R native-routine registration and disable symbol search using Rcpp::compileAttributes().

# datafsm 0.1.2

* Fixed line dropping NZV vars (line 211 of evolve_model.R)
* Changed all occurencies of 'maxfitness' to 'maxFitness' to comply with new GA version soon to be on CRAN.

# datafsm 0.1.1

Second release of package. 

* Updated vignette to properly simulate tit-for-tat data, and set a seed. Added FRD data vignette to show more advanced use of package on real data.
* Changed stop to warning if length(names) > 3. Added some text to stop() for ncol(data) != inputs.
* Made var_imp more modular. Took out core computation and put it in its own function. Added a var_imp2 function that uses output of this new importance() function and returns results for every element of state matrix, not just the colSums and puts that in a new slot in the main object called varImp2. var_imp2 returns raw performance scores.
* Added documentation for varImp2. Added check for another (4th) covariate value in C++. Test for main func now expects a warning rather than an error for when we have more than 3 predictors.
* BIGGEST CHANGE: Added evolve_model_ntimes() function to run evolve_model() ntimes and return either the best or all of them, depending on user specification. 
* In evolve_model() instead of missing(), now use is.null() so evolve_model can be called inside other functions easily.


# datafsm 0.1

First release of package.

