Cross-validation for the constrained linear least squares for compositional responses and predictors {Compositional} | R Documentation |
Cross-validation for the constrained linear least squares for compositional responses and predictors.
cv.olscompcomp(y, x, rs = 5, tol = 1e-4, nfolds = 10, folds = NULL, seed = FALSE)
y |
A matrix with compositional response data. Zero values are allowed. |
x |
A matrix with compositional predictors. Zero values are allowed. |
rs |
The number of times to run the constrained optimisation using different random starting values each time. |
tol |
The threshold upon which to stop the iterations of the constrained optimisation. |
nfolds |
The number of folds to be used. This is taken into consideration only if the folds argument is not supplied. |
folds |
If you have the list with the folds supply it here. You can also leave it NULL and it will create folds. |
seed |
If seed is TRUE the results will always be the same. |
The function performs k-fold cross-validation for the least squares regression where the beta coefficients are constained to be positive and sum to 1.
A list including:
runtime |
The runtime of the cross-validation procedure. |
kl |
The Kullback-Leibler divergences for all runs. |
js |
The Jensen-Shannon divergences for all runs. |
perf |
The average Kullback-Leibler divergence and average Jensen-Shannon divergence. |
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
ols.compcomp, cv.tflr, klalfapcr.tune
library(MASS) set.seed(1234) y <- rdiri(214, runif(3, 1, 3)) x <- as.matrix(fgl[, 2:9]) x <- x / rowSums(x) mod <- cv.olscompcomp(y, x, rs = 1, tol = 1e-4, nfolds = 5, folds = NULL, seed = 12345) mod