| nested.compare {glmnetr} | R Documentation |
Compare cross validation fit performances from a nested.glmnetr output.
Description
Compare cross-validation model fits in terms of average performances from the nested cross validation fits.
Usage
nested.compare(object, type = "devrat", digits = 4, pow = 1)
Arguments
object |
A nested.glmnetr output object. |
type |
determines what type of nested cross validation performance measures are compared. Possible values are "devrat" to compare the deviance ratios, i.e. the fractional reduction in deviance relative to the null model deviance, "agree" to compare agreement, "lincal" to compare the linear calibration slope coefficients, "intcal" to compare the linear calibration intercept coefficients, from the nested cross validation. |
digits |
digits for printing of z-scores, p-values, etc. with default of 4 |
pow |
the power to which the average of correlations is to be raised. Only applies to the "gaussian" model. Default is 2 to yield R-square but can be on to show correlations. pow is ignored for the family of "cox" and "binomial". |
Value
A printout to the R console.
See Also
nested.cis , summary.nested.glmnetr , nested.glmnetr
Examples
sim.data=glmnetr.simdata(nrows=1000, ncols=100, beta=NULL)
xs=sim.data$xs
y_=sim.data$yt
event=sim.data$event
# for this example we use a small number for folds_n to shorten run time
fit3 = nested.glmnetr(xs, NULL, y_, event, family="cox", folds_n=3)
nested.compare(fit3)