Package slamR details
Structured Latent Attribute Models in R
This package implements fast algorithms to fit structured
latent class models (SLAM) for high-dimensional dependent
binary data (Gu and Xu, 2019,'JMLR'). SLAMs are a special
family of discrete latent variable models widely used in social
and biological sciences. The goal is to learn from
high-dimensional data the signi
Maintainer: Zhenke Wu < zhenkewu at umich.edu >
From within R, enter citation('slamR')
To cite package 'slamR' in publications use:
Zhenke Wu, Yuqi Gu and Gongjun Xu (2020). slamR: Structured Latent
Attribute Models in R. R package version 0.2.1.
https://github.com/zhenkewu/slamR
A BibTeX entry for LaTeX users is
@Manual{,
title = {slamR: Structured Latent Attribute Models in R},
author = {Zhenke Wu and Yuqi Gu and Gongjun Xu},
year = {2020},
note = {R package version 0.2.1},
url = {https://github.com/zhenkewu/slamR},
}
If you have any problems with this package you can open a new issue or check the already existing ones here.
To install this package, start R and enter:
source("https://oslerinhealth.org/oslerLite.R")
# Default Install
osler_install('slamR')
# from GitHub
osler_install('slamR', release = "stable", release_repo = "github")
osler_install('slamR', release = "current", release_repo = "github")
More detailed installation instructions can be found here.
Initially submitted on | April 28 2021 10:00AM |
Last updated on | April 28 2021 10:00AM |
Package type | standard |
Source GitHub | https://github.com/zhenkewu/slamR GitHub |
OslerinHealth GitHub | https://github.com/oslerinhealth/slamR GitHub |
Depends | R (3.5.0) |
Imports | matrixStats (0.52.2), Rcpp (0.12.15), stats (3.4.1), graphics (3.4.1), grDevices (3.4.1) |
LinkingTo | Rcpp, RcppArmadillo |
Suggests | knitr, testthat, bibtex, knitcitations, rmarkdown, ars (0.5), RcppArmadillo (0.8.300.1.0) |