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miceFast 0.8.2

  • simplified naive_fill_NA, It is a regular sampling imputation now.
  • Fixed dontrun examples.
  • replace ggplot2::aes_string with ggplot2::aes, as the former is depreciated.
  • regenerate performance benchmarks on R 4.2.1.
  • styler over the code.
  • improve documentation.

miceFast 0.8.1

  • tinyverse world, less dependencies.
  • fixed imputations for character variables under linear models.
  • speed up the pmm model.
  • more tests, higher covr.
  • rerun performance tests.

miceFast 0.7.1

  • update URL inside README.

miceFast 0.7.0

  • improve coverage.
  • use drop = FALSE when subsetting the data.frame
  • healthy DESCRIPTION file, fix spaces.
  • more input validation.

miceFast 0.6.8

  • update broken vignette links

miceFast 0.6.6

  • solve broken UpSetR::upset reference links

miceFast 0.6.5

  • upset_NA based on UpSetR::upset plot function
  • compare_imp plot function
  • new logo
  • remove times argument

miceFast 0.6.2

  • R CRAN r-oldrel-windows-ix86+x86_64 problems

miceFast 0.6.1

  • lifecycle problems

miceFast 0.6.0

  • fill_NA_N has a new model which is pmm - predictive mean matching
  • fast PMM - presorting and binary search
  • naive_fill_NA - auto function for data.frames - bayes mean and lda
  • ridge argument for lm models - adding small disturbance to diag of X'X
  • lm_bayes provide more disturbance
  • new tests
  • codecov

miceFast 0.5.1

  • remove old urls form vignettes

miceFast 0.5.0

  • providing a more comfortable environment for data.table/dplyr users
  • expand vignette and documentation
  • updated performance benchmarks
  • fix a glitch - e.g. lack of correct warning for a lda model with zero variance variables

miceFast 0.2.1-3

  • data.table problem - jump to R 3.5.0
  • valgrind - a lot of optimizations - problem with arma::exp and arma::randn
  • optimize a lot of code
  • methods/functions resistant to glitches

miceFast 0.2.0

  • fix imputations with a grouping variable - error if there is precisly one NA at any group
  • add data.table to benchmarks - model with a grouping variable
  • add R functions (fill_NA_N,fill_NA,VIF) which could be used by a data.table user

miceFast 0.1.0

  • add impute_N method - optimized multiple imputations
  • add vif method - Variance inflation factors

miceFast 0.0.3

  • vignette,readme,description,todo

miceFast 0.0.2

  • adjust to solaris
  • reference - set a grouping variable by a reference but as a numeric vector - integer vector do not work (randomly lost pointer)