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

Last updated: November 22,2024

1. Install "r-cran-dynlm" package

This is a short guide on how to install r-cran-dynlm on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                r-cran-dynlm
            
                    
    
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2. Uninstall "r-cran-dynlm" package

Please follow the steps below to uninstall r-cran-dynlm on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                r-cran-dynlm
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the r-cran-dynlm package on Ubuntu 20.10 (Groovy Gorilla)

Package: r-cran-dynlm
Architecture: all
Version: 0.3.6-2build1
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: 91
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-zoo, r-cran-car (>= 2.0-0), r-cran-lmtest
Suggests: r-cran-sandwich, r-cran-strucchange
Filename: pool/universe/r/r-cran-dynlm/r-cran-dynlm_0.3.6-2build1_all.deb
Size: 54788
MD5sum: 12a31817f08fd2a673f00b82923eaf26
SHA1: a8b7a42e5151d553ceadfaa8281a647b0d767ba6
SHA256: 68659f6a34588bb1e01547434e2251282265e47a58ad0c7b5795f5929fbb1cbb
SHA512: fc79cabf7e0543bf84a57794dddfde33d82fdd92a0302958bf06dfca45f709b6a611e808a49374657efe3961e842f706f4c9be1cdacb18e6fd03f3f4b8d1081a
Homepage: https://cran.r-project.org/package=dynlm
Description-en: GNU R package for dynamic linear models and time series regression
This R package provides a user-friendly interface for fitting dynamic linear
models and time series regression relationships
.
The interface and internals of dynlm are very similar to lm, but currently
dynlm offers three advantages over the direct use of lm:
- extended formula processing;
- preservation of time series attributes;
- instrumental variables regression (via two-stage least squares).
Description-md5: 0c1f481223128c964a4d1da0c7499a31