Nothing
These routines create multiple imputations of missing at random categorical data, and create multiply imputed synthesis of categorical data, with or without structural zeros. Imputations and syntheses are based on Dirichlet process mixtures of multinomial distributions, which is a non-parametric Bayesian modeling approach that allows for flexible joint modeling, described in Manrique-Vallier and Reiter (2014) <doi:10.1080/10618600.2013.844700>.
Package details |
|
---|---|
Author | Quanli Wang, Daniel Manrique-Vallier, Jerome P. Reiter and Jingchen Hu |
Maintainer | Jingchen Hu <jingchen.monika.hu@gmail.com> |
License | GPL (>= 3) |
Version | 0.5 |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.