NAG Library Latest Content
- Active-set Method for Nonlinear Optimization: Mini Article
- General Nonlinear Data Fitting: Mini Article
- Faster Data Fitting (Calibration): Mini Article, Python Examples, Java Examples
- Fast Implied Volatilities: Mini Article, Python Examples, Java Examples
- Solving Convex and Non-convex Quadratically Constrained Quadratic Programming (QCQP) Problems: Mini Article, Python Examples, Java Examples
- Solving Convex Problems with Second-order Cone Programming (SOCP): Mini Article, Technical Poster & Python Examples
- Derivative-free Optimization Solver for Calibration Problems: Technical Poster & Mini Article
- Flexible Modelling with the NAG Optimization Modelling Suite: Mini-article & Examples
- First-order Active-set Method for Nonlinear Programming: Mini Article, Python Examples
- Nearest Correlation Matrix: Technical Poster, Python Examples, Java Examples & Mini Article
- Randomized Numerical Linear Algebra (RNLA) Algorithms: Technical Poster
- Non-negative Matrix Factorization for Analysing High-dimensional Dataset: Slide Deck & Python Examples
- Polynomial Root-finding: Blog
More NAG Library Functionality
- Algorithmic Differentiation Routines
- Derivative-free Optimization for Data Fitting
- Struve Functions
- Interior Point Method for Large Scale Linear Programming
- Interior Point Method for Nonlinear Optimization
- Semidefinite Programming (SDP)
- Three Body Problem using High-Order Runge–Kutta Interpolation
- Mixed Integer Nonlinear Programming
- Unscented Kalman Filter
- LARS / LASSO / Forward Stagewise Regression
- Change Point Analysis
- Confluent Hypergeometric Function
- Two-stage Spline Approximation to Scattered Data
- Multi-start Optimization
- Optimization for Non-negative Least Squares
- Matrix Functions
- Inhomogeneous Time Series
- Gaussian Mixture Model
- Best subset
- Bound Optimization BY Quadratic Approximation
- Linear Quantile Regression
- Sampling with Unequal Weights
- Calling random number generators from a multi-threaded environment
- Copulas
- Skipping Ahead the Mersenne Twister Random Number Generator
- Global Optimization
- Partial Least Squares / Ridge Regression
- Quantiles
- Search routines
"The code is highly reliable. The NAG Library contains some of the best algorithms available"
Fred Hickernell, Professor, Illinois Institute of Technology