Fsharp makes it easy to use numerical methods even for Van Gogh
- Another technique to find roots of equations, especially useful when working with continuous functions on closed intervals.
- Used to find roots of nonlinear equations. It is a popular technique for solving optimization problems.
- Numerical differentiation is a technique used to approximate the derivative of a function at a specific point by employing finite differences.
- The rectangle rule is the simplest method of approximating the value of a definite integral. It approximates the region under the graph of the function
f(x)as a single rectangle.
- The trapezoidal rule is a technique for approximating the definite integral. It approximates the region under the graph of the function
f(x)as a trapezoid and calculating its area.
- Simpson's rule is a technique for approximating the definite integral. It approximates the region under the graph of the function
f(x)as a series of parabolic curves and calculating their areas.
- Iterative methods for solving systems of linear equations.
- Iterative methods for solving systems of linear equations.
- Used to solve systems of linear equations, especially useful for large matrices.
- Used to solve systems of linear equations, especially useful for large matrices.
- Used to solve ordinary differential equations, which model changes in variables over time.
- A family of methods for solving ordinary differential equations and systems of differential equations.
- Techniques to estimate intermediate values between known data points (interpolation) or to fit a curve to a dataset (regression).
- Techniques to estimate intermediate values between known data points (interpolation) or to fit a curve to a dataset (regression).
- A statistical-numerical approach for simulation and problem-solving through the generation of random numbers for integration. Monte Carlo integration is a technique for approximating the definite integral. It approximates the region under the graph of the function
f(x)as a series of random points and calculating their areas.
- A statistical-numerical approach for simulation and problem-solving through the generation of random numbers for approximating the value of π.
- Used to transform signals between the time domain and the frequency domain, essential in signal processing and dynamic systems analysis.
- Gradient descent to find minima or maxima of functions.
Feel free to contribute! If you have additional methods you'd like to add or improve existing descriptions, create a pull request, and I'll be happy to review it but try to keep your solution in the programming style of F#.