Description Usage Arguments Value Examples
This function performs a parallelized LOOCV to evaluate the prediction accuracy of a linear regression whose parameter are computed through a Steepest descent algorithm. It always uses the maximum number of cores possible.
1 | cm_pllLOOCV(y, X, b_pre, tol = 0.001, maxit = 1000)
|
y |
Response variable observations |
X |
Covariates Matrix: each column contains observations for each covariate. |
tol |
Tolerance level for the optimization process, the default is 0.001. |
maxit |
Maximum iterations number |
b: |
vector of initial parameters |
The mean squared error of prediction
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