Title: Perform JIVE Decompositions for Multi-Source Data
Author: Michael J. O'Connell and Eric F. Lock
Maintainer: Michael J. O'Connell <oconn725@umn.edu>
Description: Performs the JIVE decompositions on a list of data sets when the data share a dimension, returning low-rank matrices that capture the joint and individual structure of the data. It provides two methods of rank selection when the rank is unknown, a permutation test and a BIC selection algorithm. Also included in the package are three plotting functions for visualizing the variance attributed to each data source: a bar plot that shows the percentages of the variability attributable to joint and individual structure, a heatmap that shows the structure of the variability, and principal component plots.
Imports: SpatioTemporal, gplots, graphics, stats

Title: Perform JIVE Decomposition for Multi-Source Data
Description: Performs the JIVE decomposition on a list of data sets when the data share a dimension, returning low-rank matrices that capture the joint and individual structure of the data [O'Connell, MJ and Lock, EF (2016) <doi:10.1093/bioinformatics/btw324>]. It provides two methods of rank selection when the rank is unknown, a permutation test and a BIC selection algorithm. Also included in the package are three plotting functions for visualizing the variance attributed to each data source: a bar plot that shows the percentages of the variability attributable to joint and individual structure, a heatmap that shows the structure of the variability, and principal component plots.
Imports: SpatioTemporal, gplots, abind, graphics, stats

Authors@R: c(person("Michael J.", "O'Connell", role=c("aut","cre"),
Author: Michael J. O'Connell [aut, cre],
Maintainer: Michael J. O'Connell <oconnemj@miamioh.edu>
Description: Performs the Joint and Individual Variation Explained (JIVE) decomposition on a list of data sets when the data share a dimension, returning low-rank matrices that capture the joint and individual structure of the data [O'Connell, MJ and Lock, EF (2016) <doi:10.1093/bioinformatics/btw324>]. It provides two methods of rank selection when the rank is unknown, a permutation test and a Bayesian Information Criterion (BIC) selection algorithm. Also included in the package are three plotting functions for visualizing the variance attributed to each data source: a bar plot that shows the percentages of the variability attributable to joint and individual structure, a heatmap that shows the structure of the variability, and principal component plots.