aicreg |
Identify model based upon AIC criteria from a stepreg() putput |
best.preds |
Get the best models for the steps of a stepreg() fit |
cox.sat.dev |
Calculate the CoxPH saturated log-likelihood |
cv.glmnetr |
Get a cross validation informed relaxed lasso model fit. |
cv.stepreg |
Cross validation informed stepwise regression model fit. |
difftime1 |
Get elapsed time in c(hour, minute, secs) |
difftime2 |
Output to console the elapsed and split times |
getlamgam |
get numerical values for lam and gam |
glmnetr |
Fit relaxed part of lasso model |
glmnetr.compcv |
Compare cross validation fits from a nested.glmnetr output. |
glmnetr.compcv0 |
A glmnetr specifc paired t-test |
glmnetr.simdata |
Generate example data |
glmnetrll_1fold |
Evaluate fit of leave out fold |
glmnetr_devratio |
Get Deviance ratio. |
nested.glmnetr |
Using nested cross validation, describe the fit of a cross validation informed relaxed lasso model fit. |
plot.cv.glmnetr |
Plot cross-validation deviances, or model coefficients. |
plot.glmnetr |
Plot the relaxed lasso coefficients. |
plot.nested.glmnetr |
Plot the cross validated relaxed lasso deviances or coefficients from a nested.glmnetr call. See plot.cv.glmnetr(). |
predict.cv.glmnetr |
Give predicteds based upon a cv.glmnetr() output object. |
predict.cv.stepreg |
Beta's or predicteds based upon a cv.stepreg() output object. |
predict.glmnetr |
Get predicteds or coefficients using a glmnetr output object |
predict.nested.glmnetr |
Give predicteds based upon the cv.glmnet output object contained in the nested.glmnetr output object. |
preds_1 |
Get predictors form a stepwise regression model. |
stepreg |
Fit the steps of a stepwise regression. |
summary.cv.glmnetr |
Output summary of a cv.glmnetr() output object. |
summary.cv.stepreg |
Summarize results from a cv.stepreg() output object. |
summary.nested.glmnetr |
Summarize a a nested.glmnetr() output object |
summary.stepreg |
Briefly summarize steps in a stepreg() output object, i.e. a stepwise regression fit |