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- Perform a binned fit to the IDataPointSet dataPointSet line (java,pnut)
- Create a scripted second order polynomial model and perform a binned fit to the dataPointSet parabola IDataPointSet (java,pnut)
- Perform two separate binned fits to the histogram gauss Sum Hist by restricting the axis range to only one gaussian at a time. Ranges can be controlled via the IFitData interface (java,pnut) An alternative way is to perform two projections of the tuple's column gaussSum onto IHistogram1Ds by filtering out the unwanted range, performing then the fit over the whole range of the histograms. Filtering on the tuples is done with IFilter and IEvaluator interfaces (java,pnut)
- Extend example 3 by creating a scripted sum of two gaussians to fit the histogram gauss Sum Hist over the whole range using the two previous fits to extract the starting values of the parameters (java,pnut)
- By filtering on the signal part of the tuple's column signalAndBkg project the lifetime column onto an IHistogram1D and fit it with an exponential distribution (either scripted or using the built-in one) (java,pnut)
- Project the tuple's column doubleGauss onto a IHistogram1D and perform a binned fit with the scripted function created in example 4 setting as a constraints that the two gaussians have the same mean (java,pnut)
- Extend exercise 6: use the fitted parameters from the binned fit to initialize an unbinned maximum likelihood fit to the tuple's column doubleGauss (java,pnut)
It is possible to perform some of the above exercises (the easier ones) through the GUI, by graphically manipulating functions and controlling the fit.