miceRanger

Multiple Imputation has been shown to be a flexible method to impute missing values by Van Buuren (2007) doi:10.1177/0962280206074463. Expanding on this, random forests have been shown to be an accurate model by Stekhoven and Buhlmann doi:10.48550/arXiv.1105.0828 to impute missing values in datasets. They have the added benefits of returning out of bag error and variable importance estimates, as well as being simple to run in parallel.

Last 30 days

This package has been downloaded 441 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 12 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 5,660 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was May 31, 2024 with 71 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.