Package: lvmcomp
Type: Package
Title: Stochastic EM Algorithms for Latent Variable Models with a
        High-Dimensional Latent Space
Version: 1.2
Date: 2018-12-19
Authors@R: c(
    person("Siliang", "Zhang", , "zhangsiliang123@gmail.com", c("aut", "cre")),
    person("Yunxiao", "Chen", , role = "aut"),
    person("Jorge", "Nocedal", , role = "cph"),
    person("Naoaki", "Okazaki", , role= "cph")
    )
Author: Siliang Zhang [aut, cre],
  Yunxiao Chen [aut],
  Jorge Nocedal [cph],
  Naoaki Okazaki [cph]
Description: Provides stochastic EM algorithms for latent variable models
    with a high-dimensional latent space. So far, we provide functions for confirmatory item
    factor analysis based on the multidimensional two parameter logistic (M2PL) model and the 
    generalized multidimensional partial credit model. These functions scale well for problems
    with many latent traits (e.g., thirty or even more) and are virtually tuning-free.
    The computation is facilitated by multiprocessing 'OpenMP' API.
    For more information, please refer to:
    Zhang, S., Chen, Y., & Liu, Y. (2018). An Improved Stochastic EM Algorithm for Large-scale
    Full-information Item Factor Analysis. British Journal of Mathematical and Statistical
    Psychology. <doi:10.1111/bmsp.12153>.
Maintainer: Siliang Zhang <zhangsiliang123@gmail.com>
URL: https://github.com/slzhang-fd/lvmcomp
BugReports: https://github.com/slzhang-fd/lvmcomp/issues
License: GPL-3
LazyData: true
Depends: R (>= 3.1)
Imports: Rcpp (>= 0.12.17), coda (>= 0.19-1), stats
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.0
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2018-12-19 05:34:41 UTC; siliangzhang
Repository: CRAN
Date/Publication: 2018-12-30 23:00:02 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-03 07:43:36 UTC; windows
Archs: i386, x64
