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@@ -715,6 +715,3 @@ For a model with two POIs it is often useful to look at the how well we are able
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- Run a 2D likelihood scan in `r_ggH` and `r_bbH`. You can start with around 100 points but may need to increase this later too see more detail in the resulting plot.
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- Have a look at the output limit tree, it should have branches for each POI as well as the usual deltaNLL value. You can use TTree::Draw to plot a 2D histogram of deltaNLL with `r_ggH` and `r_bbH` on the axes.
Copy file name to clipboardExpand all lines: docs/part5/longexerciseanswers.md
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@@ -148,21 +148,21 @@ Only tasks, no questions in this section
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<details>
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<summary><b>Show answer</b></summary>
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<b> As expected uncertainty you should get <code> -0.42542/+0.458748 </code> </b>
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<b> As expected uncertainty you should get <code> -0.417238/+0.450593 </code> </b>
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</details>
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- Using the RooFitResult in the `fitdiagnostics.root` file, check the post-fit value of the rateParams. To what level are the normalisations of the DY and ttbar processes constrained?
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- Using the RooFitResult in the `fitDiagnosticsTest.root` file, check the post-fit value of the rateParams. To what level are the normalisations of the DY and ttbar processes constrained?
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<details>
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<summary><b>Show answer</b></summary>
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<b> They are constrained to around 4-5% </b>
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<b> They are constrained to around 1-2% </b>
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</details>
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- To compare to the previous approach of fitting the SR only, with cross section and acceptance uncertainties restored, an additional card is provided: `datacard_part3_nocrs.txt`. Run the same fit on this card to verify the improvement of the SR+CR approach
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<details>
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<summary><b>Show answer</b></summary>
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<b> The expected uncertainty is larger with only the SR: <code> -0.463273/+0.499161 </code> compared with <code> -0.42542/+0.458748 </code> in the SR+CR approach. </b>
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<b> The expected uncertainty is larger with only the SR: <code> -0.465799/+0.502088 </code> compared with <code> -0.417238/+0.450593 </code> in the SR+CR approach. </b>
if (POI->getSize() > 1) std::cerr << "ModelConfig '" << modelConfigName_ << "' defines more than one parameter of interest. This is not supported in some statistical methods." << std::endl;
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if (mc->GetObservables() == 0) throwstd::invalid_argument("ModelConfig '"+modelConfigName_+"' does not define observables.");
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if (mc->GetPdf() == 0) throwstd::invalid_argument("ModelConfig '"+modelConfigName_+"' does not define a pdf.");
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if (auto pdf = dynamic_cast<RooSimultaneous*>(mc->GetPdf()); pdf!=nullptr) {
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if (auto pdf = dynamic_cast<RooSimultaneous*>(mc->GetPdf()); pdf!=nullptr && dynamic_cast<RooSimultaneousOpt*>(pdf)==nullptr) {
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if (rebuildSimPdf_) {
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pdf = utils::rebuildSimPdf(*mc->GetObservables(), pdf);
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