lossFunction.looe {KSPM} | R Documentation |
Computation of the leave one out error (LOOE) in kernel semi parametric model
Description
internal function to optimize model for estimating hyperparameters based on LOOE
Usage
lossFunction.looe(param. = NULL, Y. = NULL, X. = NULL,
kernelList. = NULL, n. = NULL, not.missing. = NULL,
compute.kernel. = NULL, print.lambda. = FALSE)
Arguments
param. |
initial parameter values. |
Y. |
response matrix. |
X. |
X matrix (linear part). |
kernelList. |
list of kernels (kernel part). |
n. |
nb of samples. |
not.missing. |
nb of non missing samples. |
compute.kernel. |
boolean. If TRUE, the kernel matrix is computed at each iteration. Should be TRUE when hyperparameters of kernel functions should be estimated by the model. |
print.lambda. |
boolean. If TRUE, values of tunning parameters (lambda) are printed at each iteration. |
Author(s)
Catherine Schramm, Aurelie Labbe, Celia Greenwood
[Package KSPM version 0.2.1 Index]