model_error: Model error
In spcorum/tsmvrdata: Datasets for tsmvr
Description
Usage
Arguments
Value
References
Description
Given a positive definite covariance matrix Σ, this
function calculates the model error between two matrices U
and V according to the formula
Trace [ (U-V)' Σ' Σ (U-V) ]/(mn),
where m, n are the dimensions of U (V).
If no covariance matrix is specified, the function calculates the
model error using the identity covariance matrix, which is
equivalent the normalized squared matrix error).
Usage
1
model_error(U, V, Sigma = NULL)
Arguments
U
matrix (m-by-n)
V
matrix (m-by-n)
Sigma
positive definite covariance matrix (m-by-m)
Value
The model error between U and V given
Sigma.
References
\insertRefMRCEtsmvr
spcorum/tsmvrdata documentation built on May 6, 2019, 11:17 a.m.
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Description Usage Arguments Value References
Description
Given a positive definite covariance matrix Σ, this function calculates the model error between two matrices U and V according to the formula
Trace [ (U-V)' Σ' Σ (U-V) ]/(mn),
where m, n are the dimensions of U (V). If no covariance matrix is specified, the function calculates the model error using the identity covariance matrix, which is equivalent the normalized squared matrix error).
Usage
1 | model_error(U, V, Sigma = NULL)
|
Arguments
U |
matrix (m-by-n) |
V |
matrix (m-by-n) |
Sigma |
positive definite covariance matrix (m-by-m) |
Value
The model error between U and V given
Sigma.
References
\insertRefMRCEtsmvr
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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