Table of Contents

• 0. Overview
  • 0.1 About the User Guide
  • 0.2 What's in commons-math
  • 0.3 How commons-math is organized
  • 0.4 How interface contracts are specified in commons-math javadoc
  • 0.5 Dependencies
• 1. Statistics
  • 1.1 Overview
  • 1.2 Descriptive statistics
  • 1.3 Frequency distributions
  • 1.4 Simple regression
  • 1.5 Multiple Regression
  • 1.6 Rank transformations
  • 1.7 Covariance and correlation
  • 1.8 Statistical Tests
• 2. Data Generation
  • 2.1 Overview
  • 2.2 Correlated random vectors
  • 2.3 Low discrepancy sequences
• 3. Linear Algebra
  • 3.1 Overview
  • 3.2 Real matrices
  • 3.3 Real vectors
  • 3.4 Solving linear systems
  • 3.5 Eigenvalues/eigenvectors and singular values/singular vectors
  • 3.6 Non-real fields (complex, fractions ...)
• 4. Numerical Analysis
  • 4.1 Overview
  • 4.2 Error handling
  • 4.3 Root-finding
  • 4.4 Interpolation
  • 4.5 Integration
  • 4.6 Polynomials
  • 4.7 Differentiation
• 5. Special Functions
  • 5.1 Overview
• 6. Utilities
  • 6.1 Overview
  • 6.2 Double array utilities
  • 6.3 int/double hash map
  • 6.4 Continued Fractions
  • 6.5 Binomial coefficients, factorials, Stirling numbers and other common math functions
  • 6.6 Fast mathematical functions
  • 6.7 Miscellaneous
• 7. Complex Numbers
  • 7.1 Overview
• 8. Probability Distributions
  • 8.1 Overview
  • 8.2 Generating data 'like' an input file
• 9. Fractions
  • 9.1 Overview
• 10. Transforms
• 11. Geometry
  • 11.1 Overview
• 12. Optimization
  • 12.1 Overview
  • 12.2 Univariate Functions
  • 12.3 Linear Programming
  • 12.4 Direct Methods
  • 12.5 General Case
• 13. Curve Fitting
  • 13.1 Overview
  • 13.2 Implemented Functions
  • 13.3 General Case
• 14. Least Squares
  • 14.1 Overview
  • 14.2 LeastSquaresBuilder and LeastSquaresFactory
  • 14.3 Model Function
  • 14.4 Parameters Validation
  • 14.5 Tuning
  • 14.6 Optimization Engine
  • 14.7 Solving
  • 14.8 Example
• 15. Ordinary Differential Equations Integration
  • 15.1 Overview
  • 15.2 Continuous Output
  • 15.3 Discrete Events Handling
  • 15.4 Available Integrators
  • 15.5 Derivatives
• 16. Genetic Algorithms
  • 16.1 Overview
  • 16.2 GA Framework
  • 16.3 Implementation and Examples
• 17. Filters
  • 17.1 Overview
  • 17.2 Kalman Filter
• 18. Machine Learning
  • 18.1 Overview
  • 18.2 Clustering algorithms and distance measures
  • 18.3 Implementation
• 19. Exceptions
  • 19.1 Overview
  • 19.2 Unchecked Exceptions
  • 19.3 Hierarchies
  • 19.4 Features