UPDATED RooFit Manual is now available


I would like to announce that an update of the RooFit Users Manual
has been released. You can download the p.d.f. version from the
ROOT documentation page. Click on the RooFit link on the bottom
of root.cern.ch/root/doc/RootDoc.html

One of the main new features of this manual is that each chapter
is accompanied by a set of tutorial macros that are available
in $ROOTSYS/tutorial/roofit that illustrate the functionality explained
in each chapter.

This updated version roughly doubles the page count from 69 to 134.
Another update, which will bring it to completion (and roughly
180 pages) is foreseen by the end of the year. Please note that
the tutorial macros associated with the unfinished chapter are
finished and are to a large extent self-documenting.


Table of Contents 2

What is RooFit? 4

  1. Installation and setup of RooFit 6

  2. Getting started 7
    Building a model 7
    Visualizing a model 7
    Importing data 9
    Fitting a model to data 10
    Generating data from a model 13
    Parameters and observables 13
    Calculating integrals over models 14
    Tutorial macros 16

  3. Signal and Background – Composite models 17
    Introduction 17
    Building composite models with fractions 17
    Plotting composite models 19
    Using composite models 20
    Building extended composite models 21
    Using extended composite models 23
    Note on the interpretation of fraction coefficients and ranges 23
    Navigation tools for dealing with composite objects 25
    Tutorial macros 28

  4. Choosing, adjusting and creating basic shapes 29
    What p.d.f.s are provided? 29
    Reparameterizing existing basic p.d.f.s 30
    Binding TFx, external C++ functions as RooFit functions 32
    Writing a new p.d.f. class 33
    Tutorial macros 36

  5. Convolving a p.d.f. or function with another p.d.f. 37
    Introduction 37
    Numeric convolution with Fourier Transforms 38
    Plain numeric convolution 43
    Analytical convolution 44
    Tutorial macros 48

  6. Constructing multi-dimensional models 49
    Introduction 49
    Using multi-dimensional models 50
    Modeling building strategy 52
    Multiplication 53
    Composition 54
    Conditional probability density functions 56
    Products with conditional p.d.f.s 58
    Extending products to more than two dimensions 61
    Modeling data with per-event error observables. 61
    Tutorial macros 65

  7. Working with projections and ranges 66
    Using a N-dimensional model as a lower dimensional model 66
    Visualization of multi-dimensional models 69
    Definitions and basic use of rectangular ranges 70
    Fitting and plotting with rectangular regions 73
    Ranges with parameterized boundaries 75
    Regions defined by a Boolean selection function 80
    Tuning performance of projections through MC integration 83
    Blending the properties of models with external distributions 84
    Tutorial macros 87

  8. Data modeling with discrete-valued variables 88
    Discrete variables 88
    Models with discrete observables 88
    Plotting models in slices and ranges of discrete observables 91
    Unbinned ML fits of efficiency functions using discrete observables 93
    Plotting asymmetries expressed in discrete observables 95
    Tutorial macros 96

  9. Dataset import and management 97
    Importing unbinned data from ROOT TTrees 97
    Importing unbinned data from ASCII files 98
    Importing binned data from ROOT THx histograms 98
    Manual construction, filling and retrieving of datasets 100
    Working with weighted events in unbinned data 102
    Plotting, tabulation and calculations of dataset contents 103
    Calculation of moments and standardized moments 105
    Operations on unbinned datasets 106
    Operations on binned datasets 108
    Tutorial macros 109

  10. Organizational tools 110
    Tutorial macros 110

  11. Simultaneous fits 111
    Tutorial macros 111

  12. Likelihood calculation, minimization 112
    Tutorial macros 112

  13. Special models 113
    Tutorial macros 113

  14. Validation and testing of models 114
    Tutorial macros 114

  15. Programming guidelines 115

Appendix A – Selected statistical topics 116
Appendix B – Pdf gallery 117
Appendix C – Decoration and tuning of RooPlots 118
Tutorial macros 118
Appendix D – Integration and Normalization 119
Tutorial macros 119
Appendix E – Quick reference guide 120
Plotting 120
Fitting and generating 127
Data manipulation 130
Automation tools 131