R: All correlations

allCorrelations {MatrixCorrelation} | R Documentation

## All correlations

### Description

Compare all correlation measures in the package (or a subset)

### Usage

    allCorrelations(
      X1,
      X2,
      ncomp1,
      ncomp2,
      methods = c("SMI", "RV", "RV2", "RVadj", "PSI", "r1", "r2", "r3", "r4", "GCD"),
      digits = 3,
      plot = TRUE,
      xlab = "",
      ylab = "",
      ...
    )

### Arguments

`X1` | first `matrix` to be compared (`data.frames` are also accepted).
`X2` | second `matrix` to be compared (`data.frames` are also accepted).
`ncomp1` | maximum number of subspace components from the first `matrix`.
`ncomp2` | maximum number of subspace components from the second `matrix`.
`methods` | `character` vector containing a subset of the supported methods: "SMI", "RV", "RV2", "RVadj", "PSI", "r1", "r2", "r3", "r4", "GCD".
`digits` | number of digits for numerical output.
`plot` | logical indicating if plotting should be performed (default = TRUE).
`xlab` | optional x axis label.
`ylab` | optional y axis label.
`...` | additional arguments for `SMI` or `plot`.

### Details

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

### Value

A single value measuring the similarity of two matrices.

### Author(s)

Kristian Hovde Liland

### References

- SMI: Indahl, U.G.; Næs, T.; Liland, K.H.; 2018. A similarity index for comparing coupled matrices. Journal of Chemometrics; e3049.

- 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: Mayer, CD; Lorent, J; Horgan, GW. (2011). "Exploratory analysis of multiple omics datasets using the adjusted RV coefficient". Stat Appl Genet Mol Biol. 10(14).

- PSI: Sibson, R; 1978. "Studies in the Robustness of Multidimensional Scaling: Procrustes Statistics". Journal of the Royal Statistical Society. Series B (Methodological), Vol. 40, No. 2, pp. 234-238.

- Rozeboom: Rozeboom, WW; 1965. "Linear correlations between sets of variables". Psychometrika 30(1): 57-71.

- Coxhead: Coxhead, P; 1974. "Measuring the releationship between two sets of variables". British Journal of Mathematical and Statistical Psychology 27: 205-212.

### See Also

`SMI`, `RV` (RV2/RVadj), `r1` (r2/r3/r4/GCD).

### Examples

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

    allCorrelations(X1,X2, ncomp1 = 5,ncomp2 = 5)

[Package MatrixCorrelation version 0.9.5 Index]