Description Usage Arguments Details Value Examples
cov()
and var()
form the variance-covariance matrix. cor()
forms
the correlation matrix. cov2cor()
scales a covariance matrix into a
correlation matrix.
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## S4 method for signature 'ddmatrix'
cov(x, y = NULL, use = "everything",
method = "pearson")
## S4 method for signature 'ddmatrix'
var(x, y = NULL, na.rm = FALSE, use)
## S4 method for signature 'ddmatrix'
cor(x, y = NULL, use = "everything",
method = "pearson")
## S4 method for signature 'ddmatrix'
cov2cor(V)
|
x, y, V |
numeric distributed matrices. |
use |
character indicating how missing values should be treated.
Acceptable values are the same as |
method |
character argument indicating which method should be used to
calculate covariances. Currently only "spearman" is available for
|
na.rm |
logical, determines whether or not |
cov()
forms the variance-covariance matrix. Only
method="pearson"
is implemented at this time.
var()
is a shallow wrapper for cov()
in the case of a
distributed matrix.
cov2cor()
scales a covariance matrix into a correlation matrix.
Returns a distributed matrix.
1 2 3 4 5 6 7 8 9 10 11 12 13 | spmd.code = "
library(pbdDMAT, quiet = TRUE)
init.grid()
x <- ddmatrix('rnorm', nrow=3, ncol=3), bldim=2
cv <- cov(x)
cv
finalize()
"
pbdMPI::execmpi(spmd.code = spmd.code, nranks = 2L)
|
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