mpDOACT.STATIS.core: mpDOACT.STATIS.core: Core Function for Dual STATIS (DO-ACT)...

In MExPosition: Multi-table ExPosition

Description

Performs the core of Dual STATIS on two given dataset

Usage

mpDOACT.STATIS.core(dataset1, column.design.1, dataset2, column.design.2)

Arguments

dataset1	Matrix of dataset 1
column.design.1	Column Design for dataset 1 - used to identifty the tables of the data matrix
dataset2	Matrix of dataset 2
column.design.2	Column Design for dataset 2 - used to identifty the tables of the data matrix

Details

Computation of DualSTATIS (DOSTATIS). This function should not be used independently. It should be used with mpDOACT.STATIS

Value

S.1	Inner Product: Scalar Product Matrices of dataset1
S.2	Inner Product: Scalar Product Matrices of dataset2
C	Inner Product: C Matrix
ci	Inner Product: Contribution of the rows of C
cj	Inner Product: Contribuition of the columns of C
eigs	Inner Product: Eigen Values of C
eigs.vector	Inner Product: Eigen Vectors of S
eigenValue	Inner Product: Eigen Value
fi	Inner Product: Factor Scores
tau	Inner Product: Percent Variance Explained
alphaWeights	Inner Product: Alpha Weights
betaWeights	Inner Product: Beta Weights
compromiseMatrix.1	Compromise Matrix for dataset 1
compromise.eigs.1	Compromise: Eigen Values for dataset 1
compromise.eigs.vector.1	Compromise: Eigen Vector for dataset 1
compromise.fi.1	Compromise: Factor Scores for dataset 1
Compromise.tau.1	Compromise: Percent Variance Explained for dataset 1
compromise.ci.1	Compromise: Contributions of the rows for dataset 1
compromise.cj.1	Compromise: Contributions of the Columns for dataset 1
compromiseMatrix.2	Compromise Matrix for dataset 2
compromise.eigs.2	Compromise: Eigen Values for dataset 2
compromise.eigs.vector.2	Compromise: Eigen Vector for dataset 2
compromise.fi.2	Compromise: Factor Scores for dataset 2
Compromise.tau.2	Compromise: Percent Variance Explained for dataset 2
compromise.ci.2	Compromise: Contributions of the rows for dataset 2
compromise.cj.2	Compromise: Contributions of the Columns for dataset 2
masses.1	Table: masses for dataset 1
table.eigs.1	Table: Eigen Values for dataset 1
table.eigs.vector.1	Table: Eigen Vectors for dataset 1
table.loadings.1	Table: Loadings for dataset 1
table.fi.1	Table: Factor Scores for dataset 1
table.partial.fi.1	Table: Partial Factor Scores for dataset 1
table.partial.fi.array.1	Table: Array of Partial Factor Scores for dataset 1
table.tau.1	Table: Percent Variance Explained for dataset 1
masses.2	Table: masses for dataset 2
table.eigs.2	Table: Eigen Values for dataset 2
table.eigs.vector.2	Table: Eigen Vectors for dataset 2
table.loadings.2	Table: Loadings for dataset 2
table.fi.2	Table: Factor Scores for dataset 2
table.partial.fi.2	Table: Partial Factor Scores for dataset 2
table.partial.fi.array.2	Table: Array of Partial Factor Scores for dataset 2
table.tau.2	Table: Percent Variance Explained for dataset 2

Author(s)

Cherise R. Chin Fatt and Hervé Abdi.

References

Abdi, H., Williams, L.J., Valentin, D., & Bennani-Dosse, M. (2012). STATIS and DISTATIS: Optimum multi-table principal component analysis and three way metric multidimensional scaling. Wiley Interdisciplinary Reviews: Computational Statistics, 4, 124-167

See Also

mpSTATIS, mpDOACT.STATIS

MExPosition documentation built on May 29, 2017, 2:27 p.m.