trunc_hosvd: Matrix-specific ways to estimate the rank for each mode and...
In dcgerard/hose: Higher-order spectral estimators
Description
Usage
Arguments
Author(s)
View source: R/cichocki_meet.R
Description
Matrix-specific ways to estimate the rank for each mode and then return the
truncated HOSVD.
Usage
1
2
trunc_hosvd(Y, rank_vec = NULL, method = c("pa", "bcv", "mdl"),
return_est = TRUE)
Arguments
Y
A numeric array.
rank_vec
The multilinear rank of the underlying mean. If NULL then
the multilinear rank will be estimated.
method
The way to estimate the multilinear rank if rank_vec = NULL.
The methods allowed are parallel analysis ("pa") from
num.sv, bicrossvalidation ("bcv")
from est.factor.num,
and minimum description length ("mdl") from mdl_eigen.
return_est
A logical. Should we return the final estimate from the
truncated HOSVD (TRUE) or note (FALSE)?
Author(s)
David Gerard
dcgerard/hose documentation built on Aug. 1, 2019, 12:11 a.m.
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Description Usage Arguments Author(s)
View source: R/cichocki_meet.R
Description
Matrix-specific ways to estimate the rank for each mode and then return the truncated HOSVD.
Usage
1 2 | trunc_hosvd(Y, rank_vec = NULL, method = c("pa", "bcv", "mdl"),
return_est = TRUE)
|
Arguments
Y |
A numeric array. |
rank_vec |
The multilinear rank of the underlying mean. If |
method |
The way to estimate the multilinear rank if |
return_est |
A logical. Should we return the final estimate from the
truncated HOSVD ( |
Author(s)
David Gerard
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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