missCompare

Offers a convenient pipeline to test and compare various missing data imputation algorithms on simulated and real data. These include simpler methods, such as mean and median imputation and random replacement, but also include more sophisticated algorithms already implemented in popular R packages, such as 'mi', described by Su et al. (2011) doi:10.18637/jss.v045.i02; 'mice', described by van Buuren and Groothuis-Oudshoorn (2011) doi:10.18637/jss.v045.i03; 'missForest', described by Stekhoven and Buhlmann (2012) doi:10.1093/bioinformatics/btr597; 'missMDA', described by Josse and Husson (2016) doi:10.18637/jss.v070.i01; and 'pcaMethods', described by Stacklies et al. (2007) doi:10.1093/bioinformatics/btm069. The central assumption behind 'missCompare' is that structurally different datasets (e.g. larger datasets with a large number of correlated variables vs. smaller datasets with non correlated variables) will benefit differently from different missing data imputation algorithms. 'missCompare' takes measurements of your dataset and sets up a sandbox to try a curated list of standard and sophisticated missing data imputation algorithms and compares them assuming custom missingness patterns. 'missCompare' will also impute your real-life dataset for you after the selection of the best performing algorithm in the simulations. The package also provides various post-imputation diagnostics and visualizations to help you assess imputation performance.

Last 30 days

This package has been downloaded 247 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 3,708 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 33 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.