Hi Friends, Have a look over R package "imputeTestbench". It provides a Test bench for comparison of missing data imputation models/methods. It compares imputing methods with reference to RMSE, MAE or MAPE parameters. It allows to add new proposed methods to test bench and to compare with other methods. The function 'append_method()' allows to add multiple numbers of methods to the existing methods available in test bench.
CRAN: https://cran.r-project.org/package=imputeTestbench GitHub: https://github.com/neerajdhanraj/imputeTestbench How to Use: https://www.researchgate.net/publication/305767990_R_package_%27imputeTestbench%27_as_a_Testbench_to_compare_missing_value_imputation_methods The current version is talking about univariate dataset imputation. Very next version will allow user to operate it on any type of dataset including multivariate datset. For more detail contact me at: http://www.neerajbokde.com/ -- Regards , *Neeraj Dhanraj Bokde * *M.E. Embedded System* *Birla Institute of Technology & Science,* Pilani Pilani Campus , Rajasthan, India Phone: *+91 9028415974* Email: h2012...@pilani.bits-pilani.ac.in; *neerajdhan...@gmail.com <neerajdhan...@gmail.com>* Website: http://www.neerajbokde.com [[alternative HTML version deleted]] _______________________________________________ R-packages mailing list r-packa...@r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
