PReMiuM: An R Package for Profile Regression Mixture Models Using Dirichlet Processes.
PReMiuM: An R Package for Profile Regression Mixture Models Using Dirichlet Processes.
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DOI：
10.18637/jss.v064.i07
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发表时间：
2015-03-20
影响因子：
5.8
通讯作者：
Richardson S
中科院分区：
文献类型：
--
作者：
Liverani S;Hastie DI;Azizi L;Papathomas M;Richardson S
PReMiuM是最近开发的R包贝叶斯聚类使用Dirichlet过程混合模型。该模型是回归模型的替代模型，通过聚类成员关系将响应向量与协变量数据非参数化地联系起来。该软件包允许二进制，分类，计数和连续响应，以及连续和离散协变量。此外，可以对响应进行预测，并处理协变量的缺失值。几个采样器和标签切换移动沿着实施诊断工具，以评估收敛。还提供了一些用于输出后处理的R函数。除了拟合混合物之外，还可能需要确定哪些协变量主动驱动混合物成分。这在包中作为变量选择实现。
PReMiuM is a recently developed R package for Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vector to covariate data through cluster membership. The package allows binary, categorical, count and continuous response, as well as continuous and discrete covariates. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection.