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.

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