matrix_variability: Compute "variance" of the matrices using Frobenius norm....
In bwrc/cocoreg-r: Extract Shared Variation in Collections of Data Sets Using Regression Models
Description
Usage
Arguments
Value
Description
Compute "variance" of the matrices using Frobenius norm.
Variance is by default computed with respect to the mean of the matrices.
Usage
1
2
matrix_variability(mat_lst, mean_mat = apply(abind::abind(mat_lst, along = 3),
c(1, 2), mean))
Arguments
mat_lst
A [1,M] list of [I,J] matrices from which variability should
be computed
mean_mat
A [I,J] matrix describing the mean observation for mat_lst.
Value
A list with elements
fbnorm
Frobenius norm values for each of the matrices
diff
[I,J,M] matrix of differences mat_lst-mean_mat
bwrc/cocoreg-r documentation built on May 13, 2019, 9:09 a.m.
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Description Usage Arguments Value
Description
Compute "variance" of the matrices using Frobenius norm. Variance is by default computed with respect to the mean of the matrices.
Usage
1 2 | matrix_variability(mat_lst, mean_mat = apply(abind::abind(mat_lst, along = 3),
c(1, 2), mean))
|
Arguments
mat_lst |
A [1,M] list of [I,J] matrices from which variability should be computed |
mean_mat |
A [I,J] matrix describing the mean observation for mat_lst. |
Value
A list with elements
fbnorm |
Frobenius norm values for each of the matrices |
diff |
[I,J,M] matrix of differences mat_lst-mean_mat |
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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