cv.iregnet: Cross-validation for iregnet
In anujkhare/iregnet: Regularized interval regression

First fit iregnet to the entire data set, then use K-fold cross-validation to estimate the validation error of each lambda parameter.

1	cv.iregnet(x, y, family, nfolds, foldid, ...)

`x`	numeric matrix of input features (n x p)
`y`	numeric matrix of output variables (n x 2)
`family`	gaussian, logistic
`nfolds`	positive integer between 2 and n, by default 10.
`foldid`	integer vector of length n (fold for each observation), by default we use nfolds.
`...`	passed to iregnet for both the full and cv fits.