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datafsm 0.2.4

Fix error in testing where I created a matrix from a vector of length 8 specifying 2 columns and 2 rows.
Fix obsolete URL http://www.jstatsoft.org to https://www.jstatsoft.org.
Use new \doi tag for sources in Rd documentation where the URL pointed to https://doi.org/.

datafsm 0.2.3

Replace dependency on the tidyverse package with dependencies on the specific packages from tidyverse: dplyr, tidyr, and purrr.

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 data set with iterated prisonerâs dilemma games from Nay and Vorobeychik (2016).

datafsm 0.2.1

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 occurrences 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 function 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() n times 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.

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