ccorFun: Evaluate the smallest canonical correlation for two set of...
In TOSI: Two-Directional Simultaneous Inference for High-Dimensional Models
ccorFun R Documentation
Evaluate the smallest canonical correlation for two set of variables
Description
Evaluate the smallest canonical correlation for two set of variables, each set of variables is represented by a matrix whose columns are variables.
Usage
ccorFun(hH, H)
Arguments
hH
a n-by-q matrix, one set of q variables.
H
a n-by-q matrix, the other set of q variables.
Value
return a scalar value, the smallest canonical correlation.
Note
nothing
Author(s)
Liu Wei
See Also
cancor.
Examples
dat <- gendata_Fac(n = 300, p = 500)
res <- gsspFactorm(dat$X)
ccorFun(res$hH, dat$H0)
TOSI documentation built on Feb. 16, 2023, 7:46 p.m.
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| ccorFun | R Documentation |
Evaluate the smallest canonical correlation for two set of variables
Description
Evaluate the smallest canonical correlation for two set of variables, each set of variables is represented by a matrix whose columns are variables.
Usage
ccorFun(hH, H)
Arguments
hH |
a |
H |
a |
Value
return a scalar value, the smallest canonical correlation.
Note
nothing
Author(s)
Liu Wei
See Also
cancor.
Examples
dat <- gendata_Fac(n = 300, p = 500) res <- gsspFactorm(dat$X) ccorFun(res$hH, dat$H0)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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