How to Install and Uninstall libroot-math-splot5.34 Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: December 26,2024

1. Install "libroot-math-splot5.34" package

This guide let you learn how to install libroot-math-splot5.34 on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                libroot-math-splot5.34
            
                    
    
    Copied

2. Uninstall "libroot-math-splot5.34" package

Here is a brief guide to show you how to uninstall libroot-math-splot5.34 on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                libroot-math-splot5.34
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the libroot-math-splot5.34 package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: libroot-math-splot5.34
Priority: optional
Section: universe/libs
Installed-Size: 157
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Architecture: amd64
Source: root-system
Version: 5.34.30-0ubuntu8
Depends: libc6 (>= 2.4), libgcc1 (>= 1:3.0), libroot-core5.34 (>= 5.34.30), libroot-hist5.34 (>= 5.34.30), libroot-math-mathcore5.34 (>= 5.34.30), libroot-math-matrix5.34 (>= 5.34.30), libroot-tree-treeplayer5.34 (>= 5.34.30), libroot-tree5.34 (>= 5.34.30), libstdc++6 (>= 4.1.1)
Filename: pool/universe/r/root-system/libroot-math-splot5.34_5.34.30-0ubuntu8_amd64.deb
Size: 38780
MD5sum: 3a63256a77c642f81dd31a62ae0b2edd
SHA1: eb36bb5907931aaa9858a6fe648021c265a8e277
SHA256: 4f910fb73ed3d9077ca6bbd32d63090729029e47cbca9d67797bd28cb7629275
Description-en: Splot library for ROOT
The ROOT system provides a set of OO frameworks with all the
functionality needed to handle and analyze large amounts of data
efficiently.
.
A common method used in High Energy Physics to perform measurements
is the maximum Likelihood method, exploiting discriminating variables
to disentangle signal from background. The crucial point for such an
analysis to be reliable is to use an exhaustive list of sources of
events combined with an accurate description of all the Probability
Density Functions (PDF).
.
To assess the validity of the fit, a convincing quality check is to
explore further the data sample by examining the distributions of
control variables. A control variable can be obtained for instance by
removing one of the discriminating variables before performing again
the maximum Likelihood fit: this removed variable is a control
variable. The expected distribution of this control variable, for
signal, is to be compared to the one extracted, for signal, from the
data sample. In order to be able to do so, one must be able to unfold
from the distribution of the whole data sample.
.
The SPlot method allows one to reconstruct the distributions for the
control variable, independently for each of the various sources of
events, without making use of any a priori knowledge on this
variable. The aim is thus to use the knowledge available for the
discriminating variables to infer the behaviour of the individual
sources of events with respect to the control variable.
.
SPlot is optimal if the control variable is uncorrelated with the
discriminating variables.
Description-md5: 6ba1c2ca4ff387939b55998ffc365e33
Multi-Arch: same
Homepage: http://root.cern.ch
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu