mvnimpute

Implementing a multiple imputation algorithm for multivariate data with missing and censored values under a coarsening at random assumption (Heitjan and Rubin, 1991[doi:10.1214/aos/1176348396]). The multiple imputation algorithm is based on the data augmentation algorithm proposed by Tanner and Wong (1987)[doi:10.1080/01621459.1987.10478458]. The Gibbs sampling algorithm is adopted to to update the model parameters and draw imputations of the coarse data.

Last 30 days

This package has been downloaded 125 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 2 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 1,837 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jul 21, 2024 with 69 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.