mpDISTATIS.core: mpDISTATIS.core

In MExPosition: Multi-table ExPosition

Description

mpDISTATIS.core performs the core functions of DISTATIS.

Usage

mpDISTATIS.core(data, table, sorting = 'No', normalization = 'None', 
masses = NULL, make.table.nominal=TRUE)

Arguments

data	Matrix of preprocessed data
table	Table which identifies the different tables.
sorting	a boolean. If YES, DISTATIS will by processed as a sorting task. Default is NO
normalization	Normaliztion string option: 'None' (default), 'Sum_PCA', or 'MFA'
masses	Masses: if NULL, 1/num.obs would be set by default. For customized masses, enter the vector of customized masses
make.table.nominal	a boolean. If TRUE (default), table is a vector that indicates groups (and will be dummy-coded). If FALSE, table is a dummy-coded matrix.

Details

This function should not be used directly. Please use mpDISTATIS

Value

Returns a large list of items which are also returned in mpDISTATIS.

data	Data Matrix
table	Design Matrix
normalization	Type of Normalization used.
sorting	Indicates if the task is a sorting task
S	Inner Product: Scalar Product Matrices
C	Inner Product: C Matrix
ci	Inner Product: Contribution of the rows of C
cj	Inner Product: Contribuition of the columns of C
eigs.vector	Inner Product: Eigen Vectors
eigs	Inner Product: Eigen Values
fi	Inner Product: Factor Scores
tau	Inner Product: Percent Variance Explained
alphaWeights	Alpha Weights
compromise	Compromise Matrix
compromise.eigs	Compromise: Eigen Values
compromise.eigs.vector	Compromise: Eigen Vector
compromise.fi	Compromise: Factor Scores
Compromise.tau	Compromise: Percent Variance Explained
compromise.ci	Compromise: Contributions of the rows
compromise.cj	Compromise: Contributions of the Columns
masses	Table: masses
table.eigs	Table: Eigen Values
table.eigs.vector	Table: Eigen Vectors
table.Q	Table: Loadings
table.fi	Table: Factor Scores
table.partial.fi	Table: Partial Factor Scores
table.partial.fi.array	Table: Array of Partial Factor Scores
table.tau	Table: Percent Variance Explained

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

Abdi, H., Valentin, D., Chollet, S., & Chrea, C. (2007). Analyzing assessors and products in sorting tasks: DISTATIS, theory and applications. Food Quality and Preference, 18, 627-640.

Abdi, H., & Valentin, D. (2005). DISTATIS: the analysis of multiple distance matrices. In N.J. Salkind (Ed.): Encyclopedia of Measurement and Statistics. Thousand Oaks (CA): Sage. pp. 284-290.

See Also

mpSTATIS, mpSTATIS.core, mpDISTATIS

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