CRAN/E | longit

longit

High Dimensional Longitudinal Data Analysis Using MCMC

Installation

About

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.

Key Metrics

Version 0.1.0
R ≥ 2.10
Published 2021-04-15 1111 days ago
Needs compilation? no
License GPL-3
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Maintainer

Maintainer

Atanu Bhattacharjee

atanustat@gmail.com

Authors

Atanu Bhattacharjee

aut / cre / ctb

Akash Pawar

aut / ctb

Bhrigu Kumar Rajbongshi

aut / ctb

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 2.10

Imports

AICcmodavg
missForest
R2jags
rjags
utils