preview.cca {iSFun} | R Documentation |
Statistical description before using function iscca
Description
The function describes the basic statistical information of the data, including sample mean, sample variance of X and Y, and the first pair of canonical vectors.
Usage
preview.cca(x, y, L, scale.x = TRUE, scale.y = TRUE)
Arguments
x |
list of data matrices, L datasets of explanatory variables. |
y |
list of data matrices, L datasets of dependent variables. |
L |
numeric, number of datasets. |
scale.x |
character, "TRUE" or "FALSE", whether or not to scale the variables x. The default is TRUE. |
scale.y |
character, "TRUE" or "FALSE", whether or not to scale the variables y. The default is TRUE. |
Value
An 'preview.cca' object that contains the list of the following items.
x: list of data matrices, L datasets of explanatory variables with centered columns. If scale.x is TRUE, the columns of L datasets are standardized to have mean 0 and standard deviation 1.
y: list of data matrices, L datasets of dependent variables with centered columns. If scale.y is TRUE, the columns of L datasets are standardized to have mean 0 and standard deviation 1.
loading.x: the estimated canonical vector of variables x.
loading.y: the estimated canonical vector of variables y.
meanx: list of numeric vectors, column mean of the original datasets x.
normx: list of numeric vectors, column standard deviation of the original datasets x.
meany: list of numeric vectors, column mean of the original datasets y.
normy: list of numeric vectors, column standard deviation of the original datasets y.
See Also
See Also as iscca
.
Examples
# Load a list with 3 data sets
library(iSFun)
data("simData.cca")
x <- simData.cca$x
y <- simData.cca$y
L <- length(x)
prev_cca <- preview.cca(x = x, y = y, L = L, scale.x = TRUE, scale.y = TRUE)