CanonicalDistanceAnalysis: MANOVA and Canonical Analysis of Distances

Description Usage Arguments Details Value Note Author(s) References Examples

View source: R/CanonicalDistanceAnalysis.R

Description

Performs a MANOVA and a Canonical Analysis based on of Distance Matrices (usally for continuous data)

Usage

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CanonicalDistanceAnalysis(Prox, group, dimens = 2, Nsamples = 1000, 
PCoA = "Standard", ProjectInd = TRUE)

Arguments

Prox

A object containing proximities

group

A factor with the group structure of the rows

dimens

The dimension of the solution

Nsamples

Number of samples for the permutation test. Number of permutations.

PCoA

Type of Principal Coordinates for the Canonical Analysis calculated from the Principal coordinates of the Mean Matrix. "Standard" : Standard Principal Coordinates Analysis, "Weighted": Weighted Principal Coordinates Analysis, "WPCA")

ProjectInd

Should the individual points be Projected onto the representation For the moment only available for Continuous Data.

Details

Performs a MANOVA and a Canonical Analysis based on of Distance Matrices (usally for continuous data). The MANOVA statistics is calculated from a decomposition of the distance matrix based on a factor of a external classification. The significance of the test is calculated using a premutation test. The approach depens only on the distances and then is useful with any kind of data.

The Canonical Representation is calculated from a Principal Coordinates Analysis od the distance matrix among the means. Thus, it is only possible for continuous data. The PCoA representation can be "Standard" using the means directly, "Weighted" weighting each group with its sample size or using weighted Princiopal Components Analysis of the matrix of means.

A measure of the quality of representation of the groups is provided. When possible, the measure is also provided for the individual points.

Soon, a biplot representation will also be developed.

Value

An object of class "CanonicalDistanceAnalysis" with:

Distances

The Matrix of Distances from which the Analysis has been made

Groups

A factor containing the group struture of the individuals

TSS

Total sum of squares

BSS

Between groups sum of squares

WSS

Within groups sum of squares

Fexp

Experimental pseudo F-value

pvalue

p value based on the permutation test

Nsamples

p value based on the permutation test

ExplainedVariance

Variances explained by the PCoA

MeanCoordinates

Coordinates of the groups for the graphical representation

Qualities

Qualities of the representation of the groups

CummulativeQualities

Cummulative qualities of the representation of the groups

RowCoordinates

Coordinates of the individuals for the graphical representation

Note

The MANOVA and the representation of the means can be applied to any Distance althoug the projection of the individuals can be made only for continuous data.

Author(s)

Jose Luis Vicente Villardon

References

Gower, J. C., & Krzanowski, W. J. (1999). Analysis of distance for structured multivariate data and extensions to multivariate analysis of variance. Journal of the Royal Statistical Society: Series C (Applied Statistics), 48(4), 505-519.

Krzanowski, W. J. (2004). Biplots for multifactorial analysis of distance. Biometrics, 60(2), 517-524.

Examples

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MultBiplotR documentation built on April 6, 2021, 9:08 a.m.