Package: jmBIG Type: Package Title: Joint Longitudinal and Survival Model for Big Data Version: 0.1.3 Authors@R: c(person(("Atanu"), "Bhattacharjee", email="atanustat@gmail.com", role=c("aut", "cre","ctb")), person(("Bhrigu Kumar"), "Rajbongshi", role=c("aut","ctb")), person(("Gajendra K"), "Vishwakarma", role=c("aut","ctb"))) Maintainer: Atanu Bhattacharjee Description: Provides analysis tools for big data where the sample size is very large. It offers a suite of functions for fitting and predicting joint models, which allow for the simultaneous analysis of longitudinal and time-to-event data. This statistical methodology is particularly useful in medical research where there is often interest in understanding the relationship between a longitudinal biomarker and a clinical outcome, such as survival or disease progression. This can be particularly useful in a clinical setting where it is important to be able to predict how a patient's health status may change over time. Overall, this package provides a comprehensive set of tools for joint modeling of BIG data obtained as survival and longitudinal outcomes with both Bayesian and non-Bayesian approaches. Its versatility and flexibility make it a valuable resource for researchers in many different fields, particularly in the medical and health sciences. Imports: JMbayes2,joineRML,rstanarm,FastJM,dplyr,nlme,survival,ggplot2 License: GPL-3 Encoding: UTF-8 LazyData: true Depends: R (>= 2.10) RoxygenNote: 7.3.1 NeedsCompilation: no Author: Atanu Bhattacharjee [aut, cre, ctb], Bhrigu Kumar Rajbongshi [aut, ctb], Gajendra K Vishwakarma [aut, ctb] Packaged: 2026-06-12 08:12:10 UTC; root Config/pak/sysreqs: cmake libglpk-dev make libicu-dev libuv1-dev libxml2-dev zlib1g-dev Repository: https://atanubhattacharjee.r-universe.dev Date/Publication: 2025-01-19 21:28:41 UTC RemoteUrl: https://github.com/cran/jmBIG RemoteRef: HEAD RemoteSha: 2976b8406908e05a678acb075e2eae38aa13b7ae