Sequences, series, summability Sequences and limits Concept
Rate of convergence
Summary
The rate of convergence of a convergent sequence measures how fast its distance to the limit shrinks. One compares the error at step with a power of the error at step . The exponent is the order of convergence, such as linear or quadratic. It is the standard way to compare iterative methods in numerical analysis. Two examples are fixed-point iteration and Newton's method.
Where this leads
19 pages build on this one.
- Durand–Kerner method
- Regula falsi
- Brent's method
- Inverse iteration
- Root-finding algorithm
- Quadratic convergence of Newton's method
- Aberth method
- Gauss–Newton algorithm
- Muller's method
- Steffensen's method
- Superlinear convergence of the secant method
- Broyden's method
- Inverse quadratic interpolation
- Householder's method
- Halley's method
- Levenberg–Marquardt algorithm
- Ridders' method
- Rayleigh quotient iteration
- Laguerre's method
Further reading
About this page
| Tag | YWZQC5E54B |
|---|---|
| URI | m2://YWZQC5E54B |
| Kind | concept |
| Writing | W0 stub |
| MSC | 40A05, 65B99 |
| Same as |
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Used by
- Durand–Kerner method
- Regula falsi
- Inverse iteration
- Root-finding algorithm
- Quadratic convergence of Newton's method
- Aberth method
- Gauss–Newton algorithm
- Muller's method
- Steffensen's method
- Superlinear convergence of the secant method
- Broyden's method
- Inverse quadratic interpolation
- Householder's method
- Halley's method
- Ridders' method
- Rayleigh quotient iteration
- Laguerre's method