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peperr (version 1.2)

Parallelised Estimation of Prediction Error

Description

Designed for prediction error estimation through resampling techniques, possibly accelerated by parallel execution on a compute cluster. Newly developed model fitting routines can be easily incorporated. Methods used in the package are detailed in Porzelius Ch., Binder H. and Schumacher M. (2009) and were used, for instance, in Porzelius Ch., Schumacher M.and Binder H. (2011) .

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Version

Install

install.packages('peperr')

Monthly Downloads

414

Version

1.2

License

GPL (>= 2)

Maintainer

Frederic Bertrand

Last Published

February 27th, 2021

Functions in peperr (1.2)

complexity.LASSO

Interface for selection of optimal parameter for lasso fit
PLL.coxph

Predictive partial log-likelihood for Cox poportional hazards model
fit.coxph

Interface function for fitting a Cox proportional hazards model
aggregation.pmpec

Determine the prediction error curve for a fitted model
aggregation.brier

Determine the Brier score for a fitted model
fit.LASSO

Interface function for fitting a generalised linear model with the lasso
extract.fun

Extract functions, libraries and global variables to be loaded onto a compute cluster
plot.peperr

Plot method for peperr object
ipec

Integrated prediction error curve
predictProb.coxph

Extract predicted survival probabilities from a coxph object
pmpec

Calculate prediction error curves
predictProb

Generic function for extracting predicted survival probabilities
peperr

Parallelised Estimation of Prediction Error
perr

Prediction error estimates
resample.indices

Generation of indices for resampling Procedure
predictProb.survfit

Extract predicted survival probabilities from a survfit object
aggregation.misclass

Determine the missclassification rate for a fitted model
PLL

Generic function for extracting the predictive partial log-likelihood