NEWS.md

In pdwaggoner/hdImpute: A Batch Process for High Dimensional Imputation

NEWS

hdImpute 0.2.1

A Batch Process for High Dimensional Imputation

Changes

• Added citation onLoad message: Waggoner, P. D. (2023). A batch process for high dimensional imputation. Computational Statistics, 1-22.

• Added mad() function for evaluation by computing mean absolute differences between imputations and the original data

• Added unit testing for basic mad() functionality

• Added column-wise and row-wise NA checks for pre- and post- imputation checking:

  • check_feature_na(): find features with (specified amount of) missingness
  • check_row_na(): find number of and which rows contain any missingness

• Added two new vignettes to work examples using the new functions:

  • NA checking
  • MAD score computation

• Cleaned up DESCRIPTION, fixed typos, and some small edits

How do I get hdImpute?

A stable version of the package is released on CRAN. If you have any questions, find any bugs, have ideas for improvements, etc., please follow any of the suggestions at the bottom of the README. Thanks!

pdwaggoner/hdImpute documentation built on Sept. 2, 2024, 6:41 a.m.