How to Install and Uninstall r-cran-lava Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: May 14,2024

1. Install "r-cran-lava" package

In this section, we are going to explain the necessary steps to install r-cran-lava on Ubuntu 20.10 (Groovy Gorilla)

$ sudo apt update $ sudo apt install r-cran-lava

2. Uninstall "r-cran-lava" package

Here is a brief guide to show you how to uninstall r-cran-lava on Ubuntu 20.10 (Groovy Gorilla):

$ sudo apt remove r-cran-lava $ sudo apt autoclean && sudo apt autoremove

3. Information about the r-cran-lava package on Ubuntu 20.10 (Groovy Gorilla)

Package: r-cran-lava
Architecture: all
Version: 1.6.7-2build1
Priority: optional
Section: universe/gnu-r
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian R Packages Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 2332
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-numderiv, r-cran-survival, r-cran-squarem
Recommends: r-cran-testthat (>= 0.11), r-cran-lme4, r-cran-mets (>= 1.1)
Suggests: r-cran-kernsmooth, r-cran-matrix, r-cran-data.table, r-cran-ellipse, r-cran-fields, r-cran-foreach, r-cran-geepack, r-bioc-graph, r-cran-igraph (>= 0.6), r-cran-nlme, r-cran-polycor, r-cran-quantreg, r-cran-rgl, r-cran-zoo
Filename: pool/universe/r/r-cran-lava/r-cran-lava_1.6.7-2build1_all.deb
Size: 2160428
MD5sum: d0b3ef3a6e5b4012f0cac9b2375ccb3d
SHA1: a7ba743f2ddfc9010ab12fe1a0391969706eeb54
SHA256: dc5950e8ce6f982e487c55c9fdf0580c7d8ba77cd573abe400e8c33927b53f7c
SHA512: 6bd7d02036f78263765afdaf9e06996269ed763be4c7b31df61162cdafe613e63b9a4229cf27c69ff39b2c32e4f1faaa48c30fbf3bce67c5d39d7248f300c4f8
Homepage: https://cran.r-project.org/package=lava
Description-en: GNU R latent variable models
A general implementation of Structural Equation Models
with latent variables (MLE, 2SLS, and composite likelihood
estimators) with both continuous, censored, and ordinal
outcomes (Holst and Budtz-Joergensen (2013)
). The package also provides
methods for graph exploration (d-separation, back-door criterion),
simulation of general non-linear latent variable models, and
estimation of influence functions for a broad range of statistical
models.
Description-md5: c512b4e87f394d0391d07ed467abc0fc