Tutorials | Overview | Slide Show

Introduction

The Introductory Tutorial is the most suitable entry point for beginning users. It explains the basic concepts of RooFit and gives a tour of the available features.

• Outline
  • Purpose and implementation of RooFit
  • Probability densitity functions, likelihood fitting
  • Object-oriented data modelling
  • Probability density functions
    • Elementary operations
    • Variables: parameter or observable?
    • Building PDFs - Building blocks
    • Constructing PDFs via addition,multiplication,composition and convolution
    • Extended likelihood PDFs
  • Discrete variables and functions
  • Datasets
    • Unbinned datasets
    • Weighted unbinned datasets
    • Binned datasets
    • Importing data
    • Extending/reducing datasets
  • Fitting and generating
  • Plotting PDFs and datasets
  
  
• Presentation PDF (78 pages)
  
  
• Macros (plain source files)
  1. Elementary operations on a gaussian PDF
  2. Building more complex PDFs via addition
  3. Adding more dimensions, multiplying PDFs
  4. Extend PDFs via composition
  5. Discrete variables
  6. Convoluted PDFs
  7. Using extended likelihood
  8. Dataset operations
  9. Dependents versus parameters

Page maintained by Wouter Verkerke and David Kirkby