MatrixCorrelation (version 0.9.1)

RV: RV coefficients

Description

Three different RV coefficients: RV, RV2 and adusted RV.

Usage

RV(X1, X2)
RV2(X1, X2)
RVadjMaye(X1, X2)
RVadjGhaziri(X1, X2)
RVadj(X1, X2, version = c("Maye", "Ghaziri"))

Arguments

X1

first matrix to be compared (data.frames are also accepted).

X2

second matrix to be compared (data.frames are also accepted).

version

Which version of RV adjusted to apply: "Maye" (default) or "Ghaziri" RV adjusted is run using the RVadj function.

Value

A single value measuring the similarity of two matrices.

Details

For each of the four coefficients a single scalar is computed to describe the similarity between the two input matrices.

References

• RV: Robert, P.; Escoufier, Y. (1976). "A Unifying Tool for Linear Multivariate Statistical Methods: The RV-Coefficient". Applied Statistics 25 (3): 257-265.
• RV2: Smilde, AK; Kiers, HA; Bijlsma, S; Rubingh, CM; van Erk, MJ (2009). "Matrix correlations for high-dimensional data: the modified RV-coefficient". Bioinformatics 25(3): 401-5.
• Adjusted RV: Maye, CD; Lorent, J; Horgan, GW. (2011). "Exploratory analysis of multiple omics datasets using the adjusted RV coefficient". Stat Appl Genet Mol Biol. 10(14).
• Adjusted RV: El Ghaziri, A; Qannari, E.M. (2015) "Measures of association between two datasets; Application to sensory data", Food Quality and Preference 40 (A): 116-124.

See Also

SMI, r1 (r2/r3/r4/GCD).

Examples

X1  <- matrix(rnorm(100*300),100,300)
usv <- svd(X1)
X2  <- usv$u[,-3] %*% diag(usv$d[-3]) %*% t(usv$v[,-3])

RV(X1,X2)
RV2(X1,X2)
RVadj(X1,X2)