Cross validation for some compositional regression models {Compositional} | R Documentation |
Cross validation for some compositional regression models.
cv.comp.reg(y, x, type = "comp.reg", nfolds = 10, folds = NULL, seed = FALSE)
y |
A matrix with compositional data. Zero values are allowed for some regression models. |
x |
The predictor variable(s). |
type |
This can be one of the following: "comp.reg", "robust", "kl.compreg", "js.compreg", "diri.reg" or "zadr". |
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. |
A k-fold cross validation for a compositional regression model is performed.
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.
comp.reg, kl.compreg, compppr.tune, aknnreg.tune
y <- as.matrix( iris[, 1:3] ) y <- y / rowSums(y) x <- iris[, 4] mod <- cv.comp.reg(y, x)