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miceFast 0.9.1

Bug fixes

  • PMM returned predicted values instead of observed values (C++): The pmm model returned predicted $\hat{y}$ for missing rows instead of the nearest observed $y$ values. Now it follows Little and Rubin (2002).
  • PMM with character/factor variables (R): fill_NA_N() with model = "pmm" and a character dependent variable failed because it attempted as.numeric() on non-numeric strings, producing all NAs.
  • Character dependent variable with lm models: fill_NA() and fill_NA_N() with model = "lm_pred", "lm_bayes", or "lm_noise" silently returned all NAs when the dependent variable was character with non-numeric labels (e.g., "apple", "banana").

Documentation

  • README: added sequential-chain MI examples (dplyr and data.table) showing how to impute multiple variables and pool with Rubin's rules.
  • Introduction vignette: added full imputation workflow with sequential ordering (impute variables whose predictors are complete first), FCS (chained equations) section with data.table example, and PMM note for the OOP interface.
  • MI vignette: expanded Rubin's rules derivations, added PMM MI example using the OOP interface, expanded "Important caveat" section with OOP and data.table FCS code snippets for non-monotone patterns.
  • Documented PMM as a proper MI method throughout vignettes and README.
  • Improved prose throughout vignettes and README.

Tests

  • Added 20 PMM-specific tests (test-pmm.R): observed-value returns, factor/character support, weighted PMM, grouped data.table, reproducibility, stochasticity.
  • Added 31 FCS tests (test-fcs.R): data.table, data.frame, and OOP FCS helpers; joint-missingness handling; MI+pool workflow; comparison with mice (pooled estimates and imputed means).
  • Added tests for character dependent variables with non-numeric labels across all models and data types.
  • Test suite expanded from 243 to 311 tests.

miceFast 0.9.0

Kota Hattori, thank you for your feedback and for motivating me for this deep update.

New features

  • pool() function for combining results from multiply imputed datasets (Rubin's rules, Barnard-Rubin df adjustment). Works with lm, glm, and other models that support coef() and vcov(). Validated against mice.
  • print and summary methods for pooled results.

Bug fixes

  • fixed residual variance estimator in lm_noise and lm_bayes stochastic models: divisor changed from n-p-1 to n-p, where p already counts the intercept column supplied by the user. The previous formula over-corrected by one degree of freedom.

Documentation and internals

  • new vignette on missing data mechanisms (MCAR/MAR/MNAR) and MI workflows.
  • refactored introduction vignette with pool() examples.
  • improved README with MI section and benchmark table.
  • test suite for pool(), including comparison against mice::pool().
  • new weighted regression validation test against lm.wfit().
  • refactored C++ source code for clarity.
  • fixed typos in error messages and documentation.
  • regenerated performance benchmarks on R 4.4.3, macOS M3 Pro.

miceFast 0.8.5

  • cran related update, OMP_THREAD_LIMIT.

miceFast 0.8.4

  • fixed CRAN Notes.
  • style the cpp code.
  • VIF() should be more stable.

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)