Contents

• Foreword
  • What Minuit is intended to do.
  • What Minuit is not intended to do.
  • Further remarks.
• Minuit Basic Concepts.
  • The Organization of Minuit.
  • Internal and External Parameters.
  • Minuit Strategy.
  • Parameter Errors.
    • The Error Matrix.
    • MINOS Errors.
      • CONtour
      • MNContour
• Minuit Installation.
  • Minuit Releases.
  • Minuit Versions.
  • Interference with Other Packages
  • Floating-point Precision
• How to Use Minuit
  • The Function FCN.
  • Running Minuit in Data-driven Mode.
    • Note
    • Batch and interactive running.
• Minuit Commands
  • List of Minuit commands
• How to get the right answer from Minuit.
  • Which Minimizer to Use.
    • MIGRAD
    • MINIMIZE
    • SCAN
    • SEEK
  • Parameter Limits
    • Getting the Right Minimum with Limits.
    • Getting the right parameter errors with limits.
  • Fixing and Releasing Parameters
  • Interpretation of Parameter Errors
    • Statistical Interpretation.
    • The Reliability of Minuit Error Estimates.
  • Additional Trouble-shooting
• A complete example
  • A data-driven fit
• Interpretation of the errors on parameters as given by Minuit
  • Function normalization and [SET ERRordef]ERROR DEF
    • Chi-square normalization
    • Likelihood normalization
  • Non-linearities: [MIGrad]MIGRAD versus [HESse]HESSE versus [MINos]MINOS
    • Errors printed by Minuit
    • Errors after [MIGrad]MIGRAD (or [MINImize]MINIMIZE)
    • Errors after [HESse]HESSE
    • Errors by [MINos]MINOS
  • Multiparameter errors
    • The Error Matrix
    • [MINos]MINOS with several free Parameters
    • Probability content of confidence regions
• References
• Index