How to Install and Uninstall root-splot.x86_64 Package on Rocky Linux 8
Last updated: November 30,2024
1. Install "root-splot.x86_64" package
This is a short guide on how to install root-splot.x86_64 on Rocky Linux 8
$
sudo dnf update
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$
sudo dnf install
root-splot.x86_64
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2. Uninstall "root-splot.x86_64" package
Please follow the guidance below to uninstall root-splot.x86_64 on Rocky Linux 8:
$
sudo dnf remove
root-splot.x86_64
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$
sudo dnf autoremove
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3. Information about the root-splot.x86_64 package on Rocky Linux 8
Last metadata expiration check: 2:23:21 ago on Mon Sep 12 10:27:18 2022.
Available Packages
Name : root-splot
Version : 6.26.06
Release : 1.el8
Architecture : x86_64
Size : 79 k
Source : root-6.26.06-1.el8.src.rpm
Repository : epel
Summary : Splot library for ROOT
URL : https://root.cern/
License : LGPLv2+
Description : 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 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 behavior 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.
Available Packages
Name : root-splot
Version : 6.26.06
Release : 1.el8
Architecture : x86_64
Size : 79 k
Source : root-6.26.06-1.el8.src.rpm
Repository : epel
Summary : Splot library for ROOT
URL : https://root.cern/
License : LGPLv2+
Description : 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 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 behavior 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.