msma: Multiblock Sparse Multivariable Analysis
Version 0.7

There are several functions to implement the method for analysis in a multiblock multivariable data. If the input is only a matrix, then the principal components analysis (PCA) is implemented. If the input is a list of matrices, then the multiblock PCA is implemented. If the input is two matrices for exploratory and objective variables, then the partial least squares (PLS) analysis is implemented. If the input is two list of matrices for exploratory and objective variables, then the multiblock PLS analysis is implemented. Moreover, if the extra outcome variable is specified, then the supervised version for the methods above is implemented. For each methods, the sparse modeling is also incorporated. Functions to select the number of components and the regularized parameters are also provided.

Package details

AuthorAtsushi Kawaguchi
Date of publication2016-01-01 21:47:02
MaintainerAtsushi Kawaguchi <kawa_a24@yahoo.co.jp>
LicenseGPL (>= 2)
Version0.7
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("msma")

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msma documentation built on May 30, 2017, 2:27 a.m.