How to Install and Uninstall libt-digest-java Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: November 27,2024

1. Install "libt-digest-java" package

In this section, we are going to explain the necessary steps to install libt-digest-java on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                libt-digest-java
            
                    
    
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2. Uninstall "libt-digest-java" package

Learn how to uninstall libt-digest-java on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                libt-digest-java
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libt-digest-java package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: libt-digest-java
Priority: optional
Section: universe/java
Installed-Size: 73
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Java Maintainers
Architecture: all
Source: t-digest
Version: 1:3.0-1build1
Suggests: libt-digest-java-doc
Filename: pool/universe/t/t-digest/libt-digest-java_3.0-1build1_all.deb
Size: 49660
MD5sum: 5baf9fadee8f16d0eea95e7c2d7ad4e6
SHA1: 8ad9eae16b1623a234fd16ed3d6569d333733bd6
SHA256: 00e61350922f931e8f45239c54d0599efe4cbd6954732de00365f7f6f4db9603
Description-en: Data structure for quantiles and related rank statistics
The t-digest construction algorithm uses a variant of 1-dimensional
k-means clustering to product a data structure that is related to the
Q-digest. This t-digest data structure can be used to estimate
quantiles or compute other rank statistics. The advantage of the
t-digest over the Q-digest is that the t-digest can handle floating
point values while the Q-digest is limited to integers. With small
changes, the t-digest can handle any values from any ordered set that
has something akin to a mean. The accuracy of quantile estimates
produced by t-digests can be orders of magnitude more accurate than
those produced by Q-digests in spite of the fact that t-digests are
more compact when stored on disk.
Description-md5: 66f122eeb099f2b7c4da5fb6e8d311d8
Homepage: https://github.com/tdunning/t-digest
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu