evaluation.sum: Hierarchical Heterogeneity Regression Analysis.
In HhP: Hierarchical Heterogeneity Analysis via Penalization
View source: R/evaluation.sum.R
evaluation.sum R Documentation
Hierarchical Heterogeneity Regression Analysis.
Description
The main function for Transfer learning for tensor graphical models.
Usage
evaluation.sum(n,q,p,admmres, abic.n, admmres2, Beta0, bic.var)
Arguments
n
The sample size.
q
The dimension of type 1 features.
p
The dimension of type 2 features.
admmres
The results corresponding to lambda1.
abic.n
The BIC values.
admmres2
The results corresponding to lambda1.
Beta0
The true values of beta.
bic.var
The BIC values.
Value
A result list including: evaluating indicator
HhP documentation built on Nov. 23, 2022, 5:07 p.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
View source: R/evaluation.sum.R
| evaluation.sum | R Documentation |
Hierarchical Heterogeneity Regression Analysis.
Description
The main function for Transfer learning for tensor graphical models.
Usage
evaluation.sum(n,q,p,admmres, abic.n, admmres2, Beta0, bic.var)
Arguments
n |
The sample size. |
q |
The dimension of type 1 features. |
p |
The dimension of type 2 features. |
admmres |
The results corresponding to lambda1. |
abic.n |
The BIC values. |
admmres2 |
The results corresponding to lambda1. |
Beta0 |
The true values of beta. |
bic.var |
The BIC values. |
Value
A result list including: evaluating indicator
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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