Deploy site from ${GITHUB_REPOSITORY}@${GITHUB_SHA} hep-statistics-serialization-standard/hep-statistics-serialization-standard@1897c0c

Author: cburgard

chapters/2.1.1_fundamental_distributions/index.html

@@ -1275,7 +1275,7 @@ <h4 id="multivariate-normal-distribution">Multivariate normal distribution<a cla
 </ul>
 <h4 id="histfactory-distribution">HistFactory distribution<a class="headerlink" href="#histfactory-distribution" title="Permanent link">&para;</a></h4>
 <p>HistFactory [^hf] is a language to describe statistical models consisting only of "histograms" (which is used interchangeably with "step-functions" in this context). Each HistFactory distribution describes one "channel" or "region" of a binned measurement, containing a stack of "samples", i. e.&nbsp;binned distributions sharing the same binning (step-functions describing the signal or background of a measurement). Such a HistFactory model is shown in Figure <a href="#fig:hf-example" reference="fig:hf-example" reference-type="ref">1</a> (originally from  [^atlashzz]). Each of the contributions may be subject to <code>modifiers</code>. </p>
-<p><img alt="A binned statistical model describing a High Energy Physics measurement, in this case of the \(H\rightarrow 4l\) process by the ATLAS collaboration. Three different sample (blue, red, violet) are considered." id="fig:hf-example" src="/images/hf-example.pdf" width=".6\%" /> </p>
+<p><img alt="A binned statistical model describing a High Energy Physics measurement, in this case of the \(H\rightarrow 4l\) process by the ATLAS collaboration. Three different sample (blue, red, violet) are considered." id="fig:hf-example" src="/images/hf-example.png" width=".6\%" /> </p>
 <p>The prediction for a binned region is given as </p>
 <div class="arithmatex">\[
 \begin{aligned} \lambda(x)=\sum_{s\in\text{samples}} \left[ \left( d_s(x) + \sum_{\delta\in M_{\delta}} \delta(x,\theta_\delta) \right) \prod_{\kappa\in M_\kappa} \kappa(x,\theta_\kappa)   \right] \end{aligned} 

files/hs3.pdf

@@ -24,7 +24,7 @@
 
 
 
-        <title>HS<sup>3</sup> v0.2.9 - HEP Statistics Serialization Standard (HS3)</title>
+        <title>HS3 - HEP Statistics Serialization Standard (HS3)</title>
 
 
 
@@ -114,7 +114,7 @@
         <div class="md-header__topic" data-md-component="header-topic">
           <span class="md-ellipsis">
 
-              HS<sup>3</sup> v0.2.9
+              HS3
 
           </span>
         </div>
@@ -1039,7 +1039,7 @@ <h4 id="multivariate-normal-distribution">Multivariate normal distribution<a cla
 </ul>
 <h4 id="histfactory-distribution">HistFactory distribution<a class="headerlink" href="#histfactory-distribution" title="Permanent link">&para;</a></h4>
 <p>HistFactory <sup id="fnref:hf"><a class="footnote-ref" href="#fn:hf">11</a></sup> is a language to describe statistical models consisting only of "histograms" (which is used interchangeably with "step-functions" in this context). Each HistFactory distribution describes one "channel" or "region" of a binned measurement, containing a stack of "samples", i. e.&nbsp;binned distributions sharing the same binning (step-functions describing the signal or background of a measurement). Such a HistFactory model is shown in Figure <a href="#fig:hf-example" reference="fig:hf-example" reference-type="ref">1</a> (originally from  <sup id="fnref:atlashzz"><a class="footnote-ref" href="#fn:atlashzz">12</a></sup>). Each of the contributions may be subject to <code>modifiers</code>. </p>
-<p><img alt="A binned statistical model describing a High Energy Physics measurement, in this case of the \(H\rightarrow 4l\) process by the ATLAS collaboration. Three different sample (blue, red, violet) are considered." id="fig:hf-example" src="/images/hf-example.pdf" width=".6\%" /> </p>
+<p><img alt="A binned statistical model describing a High Energy Physics measurement, in this case of the \(H\rightarrow 4l\) process by the ATLAS collaboration. Three different sample (blue, red, violet) are considered." id="fig:hf-example" src="/images/hf-example.png" width=".6\%" /> </p>
 <p>The prediction for a binned region is given as </p>
 <div class="arithmatex">\[
 \begin{aligned} \lambda(x)=\sum_{s\in\text{samples}} \left[ \left( d_s(x) + \sum_{\delta\in M_{\delta}} \delta(x,\theta_\delta) \right) \prod_{\kappa\in M_\kappa} \kappa(x,\theta_\kappa)   \right] \end{aligned} 

images/hf-example.png

@@ -754,7 +754,7 @@
   <h1>Histfactory</h1>
 
 <p>HistFactory [^hf] is a language to describe statistical models consisting only of "histograms" (which is used interchangeably with "step-functions" in this context). Each HistFactory distribution describes one "channel" or "region" of a binned measurement, containing a stack of "samples", i. e.&nbsp;binned distributions sharing the same binning (step-functions describing the signal or background of a measurement). Such a HistFactory model is shown in Figure <a href="#fig:hf-example" reference="fig:hf-example" reference-type="ref">1</a> (originally from  [^atlashzz]). Each of the contributions may be subject to <code>modifiers</code>. </p>
-<p><img alt="A binned statistical model describing a High Energy Physics measurement, in this case of the \(H\rightarrow 4l\) process by the ATLAS collaboration. Three different sample (blue, red, violet) are considered." id="fig:hf-example" src="/images/hf-example.pdf" width=".6\%" /> </p>
+<p><img alt="A binned statistical model describing a High Energy Physics measurement, in this case of the \(H\rightarrow 4l\) process by the ATLAS collaboration. Three different sample (blue, red, violet) are considered." id="fig:hf-example" src="/images/hf-example.png" width=".6\%" /> </p>
 <p>The prediction for a binned region is given as </p>
 <div class="arithmatex">\[
 \begin{aligned} \lambda(x)=\sum_{s\in\text{samples}} \left[ \left( d_s(x) + \sum_{\delta\in M_{\delta}} \delta(x,\theta_\delta) \right) \prod_{\kappa\in M_\kappa} \kappa(x,\theta_\kappa)   \right] \end{aligned}