Description Usage Arguments Details Functions References See Also
functions used to calculate cross validation error and used by
the cv.sail
function
1 2 3 4 5 6 7 8 |
outlist |
list of cross validated fitted models. List is of length equal
to |
lambda |
a user supplied lambda sequence. Typically, by leaving this
option unspecified users can have the program compute its own lambda
sequence based on |
x |
input matrix of dimension |
y |
response variable. For |
e |
exposure or environment vector. Must be a numeric vector. Factors must be converted to numeric. |
weights |
observation weights. Default is 1 for each observation. Currently NOT IMPLEMENTED. |
foldid |
numeric vector indicating which fold each observation belongs to |
type.measure |
loss to use for cross-validation. Currently only 3
options are implemented. The default is |
grouped |
This is an experimental argument, with default |
keep |
If |
mat |
matrix of predictions |
nlams |
number of lambdas fit |
cvm |
mean cv error |
cvsd |
sd of cv error |
s |
numeric value of lambda |
The output of the cv.lspath
function only returns values for
those tuning parameters that converged. cvcompute, getmin,
lambda.interp
are taken verbatim from the glmnet
package
cvcompute
: Computations for crossvalidation error
getmin
: get lambda.min and lambda.1se
lambda.interp
: Interpolation function.
Jerome Friedman, Trevor Hastie, Robert Tibshirani (2010). Regularization Paths for Generalized Linear Models via Coordinate Descent. Journal of Statistical Software, 33(1), 1-22. http://www.jstatsoft.org/v33/i01/.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.