Description: This package provides an interface to the OAuth 1.0
specification, allowing users to authenticate via OAuth to the
Author: Jeff Gentry <geoffjentry@gmail.com>, Duncan Temple Lang
Depends: R (>= 2.12.0), RCurl (>= 1.6-4), digest, methods

Description: Provides an interface to the OAuth 1.0 specification
allowing users to authenticate via OAuth to the

Packaged: 2015-02-12 03:57:04 UTC; pablobarbera

Title: Estimation of prognostic or diagnostic capacity of microarray
Description: This package computes traditional ROC curves and time-dependent ROC curves using the cross-validation, the 0.632 and the 0.632+ estimators. The 0.632+ estimator of time-dependent ROC curve is useful to estimate the predictive accuracy of prognostic signature based on high-dimensional data. For instance, it outperforms the other approaches, especially the cross-validation solution which is often used. The 0.632+ estimators correct the area under the curve in order to adequately estimate the prognostic capacities regardless of the overfitting level. This package also allows for the construction of diagnostic or prognostic scoring systems (penalized regressions). The methodology is adapted to complete data (penalized logistic regression associated with ROC curve) or incomplete time-to-event data (penalized Cox model associated with time-dependent ROC curve).
Depends: R (>= 2.10), splines, survival, penalized, survivalROC

Title: Construction of diagnostic or prognostic scoring system and
internal validation of its discriminative capacities based on
ROC curve and 0.633+ boostrap resampling.

Authors@R: c(person("Majid", "Nabipoor", email = "nabipoor@ualberta.ca", role=c("aut", "cre","cph")),
Description: The algorithm provided in this package generates perfect sample for unimodal or multimodal posteriors. Read Once Coupling From The Past, with Metropolis-Multishift is used to generate a perfect sample for a given posterior density based on the two extreme starting paths, minimum and maximum of the most interest range of the posterior. It uses the monotone random operation of multishift coupler which allows to sandwich all of the state space in one point. It means both Markov Chains starting from the maximum and minimum will be coalesced. The generated sample is independent from the starting points. It is useful for mixture distributions too. The output of this function is a real value as an exact draw from the posterior distribution.
Collate: 'LR.R' 'multishift.R' 'M.MSH.sampler.R' 'CFTP.R'