sensory: Cluster-Wise Imputation via a PEM Algorithm

In sensory: Simultaneous Model-Based Clustering and Imputation via a Progressive Expectation-Maximization Algorithm

Description

Contains the function CUUimpute() which performs model-based clustering and imputation simultaneously.

Details

Package:	sensory
Type:	Package
Version:	1.0
Date:	2014-08-07
License:	GPL (>=2)

This package contains two data sets collected at Compusense Inc. in Guelph, Ontario, Canada, a modified version of Fisher's Irises, and the function CUUImpute().

Author(s)

Brian C. Franczak, Ryan P. Browne and Paul D. McNicholas
Maintainer: Brian C. Franczak <[e-mail]>

References

P.D. McNicholas and T.B. Murphy (2008). Parsimonious Gaussian Mixture Models. Statistics and Computing (18), 285-296.
Browne, R.P., P.D. McNicholas, and C.J. Findlay (2013). A partial EM algorithm for clustering white breads. arXiv preprint arXiv:1302.6625.

See Also

Details, examples, and references are given under CUUimpute

sensory documentation built on May 2, 2019, 4:01 p.m.