MLM_cv: Cross validation (fold-5) function for high dimension data.
In changwn/RMR: Robust Mixture Regression
MLM_cv R Documentation
Cross validation (fold-5) function for high dimension data.
Description
Cross validation (fold-5) function for high dimension data.
Usage
MLM_cv(x = NULL, y = NULL, nit = 1, nc = 2, max_iter = 50)
Arguments
x
x variable.
y
y variable.
nit
Iteration number.
nc
The number of component.
max_iter
Maximum iteration.
Value
The correlation between y and y_hat based on five fold cross validation.
changwn/RMR documentation built on March 29, 2025, 3:15 p.m.
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| MLM_cv | R Documentation |
Cross validation (fold-5) function for high dimension data.
Description
Cross validation (fold-5) function for high dimension data.
Usage
MLM_cv(x = NULL, y = NULL, nit = 1, nc = 2, max_iter = 50)
Arguments
x |
x variable. |
y |
y variable. |
nit |
Iteration number. |
nc |
The number of component. |
max_iter |
Maximum iteration. |
Value
The correlation between y and y_hat based on five fold cross validation.
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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