WebHigh-performing functions operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized. There are also optimized vector-based methods, e.g. binMeans(), madDiff() and … WebProvides a general-purpose tool for dynamic report generation in R using Literate Programming techniques.
R: Extended Joint Models for Longitudinal and Time-to-Event Data
WebJMbayes2 fits joint models using Markov chain Monte Carlo algorithms implemented in C++. Besides the main modeling function, the package also provides a number of functions to … WebDevelopement of R Functions to Estimate Complex Bayesian Regression Models. Jump to revision: Author: alexvolkmann: Date: Thu Sep 1 16:04:52 2024 UTC (4 months, 2 weeks ago): Log Message: soft fascination
Approximations to the Log-Likelihood Function in the Nonlinear …
WebAccuracy Measures {JMbayes2} R Documentation: Time-Dependent ROCs and AUCs for Joint Models Description. Using the available longitudinal information up to a starting time point, this function computes an estimate of the ROC and the AUC at a horizon time point based on joint models. Web2 JMbayes: Joint Models Using MCMC in R time-dependent Cox model (Therneau and Grambsch2000), are not optimal for measuring this association. Endogenous covariates are covariates, which are measured on the sample Web30 apr. 2014 · The R Package JMbayes for Fitting Joint Models for Longitudinal and Time-to-Event Data using MCMC Dimitris Rizopoulos Joint models for longitudinal and time-to-event data constitute an attractive modeling framework that has received a lot of interest in the recent years. softfamous ms office