Package: mlm4omics
Version: 1.3.0
Title: Multilevel Model for Multivariate Responses with Missing Values
Description: To conduct Bayesian inference regression for responses with
    multilevel explanatory variables and missing values; It uses function from
    'Stan', a software to implement posterior sampling using Hamiltonian MC and
    its variation Non-U-Turn algorithms. It implements the posterior sampling 
    of regression coefficients from the multilevel regression models. 
    The package has two main functions to handle not-missing-at-random missing 
    responses and left-censored with not-missing-at random responses. 
    The purpose is to provide a similar format as the other R regression 
    functions but using 'Stan' models.
Authors@R: c(person("Irene", "Zeng", role = c("aut", "cre"),
            email = "i.zeng@auckland.ac.nz"),
            person("Thomas", "Lumley", role = "ctb", email = "t.lumey@auckland.ac.nz"))
Maintainer: Irene SL Zeng <i.zeng@auckland.ac.nz>
License: GPL-3
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 3.5.0), Rcpp (>= 0.12.17), methods, stats
Imports: rstan (>= 2.17.3),rstantools (>=
        1.5.0),MASS,Matrix,stats4,ggplot2
LinkingTo: StanHeaders (>= 2.17.2), rstan (>= 2.17.3), BH (>=
        1.66.0-1), Rcpp (>= 0.12.17), RcppEigen (>= 0.3.3.4.0)
Suggests: testthat, BiocStyle, knitr, rmarkdown, roxygen2 (>= 5.0.0)
URL: https://doi.org/10.1101/153049
RoxygenNote: 6.0.1
biocViews: ImmunoOncology,
        Bayesian,CopyNumberVariation,Classification,Regression,MassSpectrometry,Proteomics,Software
bugReport: https://github.com/ireneslzeng/mlmm/issues
VignetteBuilder: knitr
SystemRequirements: GNU make
NeedsCompilation: yes
git_url: https://git.bioconductor.org/packages/mlm4omics
git_branch: master
git_last_commit: 754d8b6
git_last_commit_date: 2019-05-02
Date/Publication: 2019-05-14
Packaged: 2019-05-15 04:43:59 UTC; biocbuild
Author: Irene Zeng [aut, cre],
  Thomas Lumley [ctb]
Built: R 3.6.0; i386-w64-mingw32; 2019-05-15 12:23:51 UTC; windows
Archs: i386, x64
