corDiss {resemble}R Documentation

Correlation and moving correlation dissimilarity measurements (corDiss)

Description

Computes correlation and moving correlation dissimilarity matrices.

Usage

corDiss(Xr, X2 = NULL, ws = NULL, 
        center = TRUE, scaled = TRUE)

Arguments

Xr

a matrix (or data.frame) containing the (reference) data.

X2

an optional matrix (or data.frame) containing data of a second set of observations (samples).

ws

for moving correlation dissimilarity, an odd integer value which specifies the window size. If ws = NULL, then the window size will be equal to the number of variables (columns), i.e. instead moving correlation, the normal correlation will be used. See details.

center

a logical indicating if the spectral data Xr (and X2 if specified) must be centered. If X2 is specified the data is scaled on the basis of Xr \cup X2.

scaled

a logical indicating if Xr (and X2 if specified) must be scaled. If X2 is specified the data is scaled on the basis of Xr \cup X2.

Details

The correlation dissimilarity cd between two obsvervations x_i and x_j is computed as follows:

cd(x_i, x_j) = \frac{1}{2}(1 - cor(x_i, x_j))

The avobe formlula is used when ws = NULL. On the other hand (when ws != NULL) the moving correlation dissimilarity mcd between two obsvervations x_i and x_j is computed as follows:

mcd(x_i, x_j) = \frac{1}{2 ws}∑_{k=1}^{p-ws}(1 - cor(x_{i,(k:k+ws)}, x_{j,(k:k+ws)}))

where ws represents a given window size which rolls sequantially fom 1 up to p - ws and p is the number of variables of the observations. The function does not accept input data containing missing values.

Value

a matrix of the computed dissimilarities.

Author(s)

Antoine Stevens and Leonardo Ramirez-Lopez

Examples

## Not run: 
require(prospectr)
data(NIRsoil)

Xu <- NIRsoil$spc[!as.logical(NIRsoil$train),]
Xr <- NIRsoil$spc[as.logical(NIRsoil$train),]

corDiss(Xr = Xr)

corDiss(Xr = Xr, X2 = Xu)

corDiss(Xr = Xr, ws = 41)

corDiss(Xr = Xr, X2 = Xu, ws = 41) 

## End(Not run)

[Package resemble version 1.2.2 Index]