Package: longit 0.1.0

Atanu Bhattacharjee

longit: High Dimensional Longitudinal Data Analysis Using MCMC

High dimensional longitudinal data analysis with Markov Chain Monte Carlo(MCMC). Currently support mixed effect regression with or without missing observations by considering covariance structures. It provides estimates by missing at random and missing not at random assumptions. In this R package, we present Bayesian approaches that statisticians and clinical researchers can easily use. The functions' methodology is based on the book "Bayesian Approaches in Oncology Using R and OpenBUGS" by Bhattacharjee A (2020) <doi:10.1201/9780429329449-14>.

Authors:Atanu Bhattacharjee [aut, cre, ctb], Akash Pawar [aut, ctb], Bhrigu Kumar Rajbongshi [aut, ctb]

longit_0.1.0.tar.gz
longit_0.1.0.tar.gz(r-4.5-noble)longit_0.1.0.tar.gz(r-4.4-noble)
longit_0.1.0.tgz(r-4.4-emscripten)longit_0.1.0.tgz(r-4.3-emscripten)
longit.pdf |longit.html✨
longit/json (API)

# Install 'longit' in R:
install.packages('longit', repos = 'https://cloud.r-project.org')
Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

jagscpp

1.00 score 186 downloads 10 exports 39 dependencies

Last updated 4 years agofrom:2aa442df66. Checks:1 OK, 2 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 08 2025
R-4.5-linuxNOTEMar 08 2025
R-4.4-linuxNOTEMar 08 2025

Exports:BysmixedBysmxDICBysmxHPDBysmxmsBysmxmsscreghdmarjghdmnarjgmvncovar1mvncovar2

Dependencies:abindAICcmodavgbootclicodacodetoolsdigestdoRNGforeachglueiteratorsitertoolslatticelifecyclemagrittrMASSMatrixmissForestnlmeR2jagsR2WinBUGSrandomForestrbibutilsRcppRcppArmadilloRcppEigenRdpackreformulasrjagsrlangrngtoolsstringistringrsurvivalTMBunmarkedvctrsVGAMxtable

Citation

To cite package ‘longit’ in publications use:

Bhattacharjee A, Pawar A, Rajbongshi B (2021). longit: High Dimensional Longitudinal Data Analysis Using MCMC. R package version 0.1.0, https://CRAN.R-project.org/package=longit.

Corresponding BibTeX entry: 

  @Manual{,
    title = {longit: High Dimensional Longitudinal Data Analysis Using
      MCMC},
    author = {Atanu Bhattacharjee and Akash Pawar and Bhrigu Kumar
      Rajbongshi},
    year = {2021},
    note = {R package version 0.1.0},
    url = {https://CRAN.R-project.org/package=longit},
  }