Approximations and expansions Interpolation Concept
Polynomial interpolation
Summary
Polynomial interpolation finds a polynomial whose graph passes through finitely many given points. Through points with distinct first coordinates there is exactly one polynomial of degree at most . Lagrange interpolation gives an explicit formula for it. It is a basic tool to approximate functions, to derive numerical integration rules and to reconstruct polynomials from their values.
Where this leads
20 pages build on this one.
- Newton polynomial
- Birkhoff interpolation
- Mean value theorem for divided differences
- Multivariate interpolation
- Direct collocation
- Hermite interpolation
- Muller's method
- Interpolation error formula
- Neville's algorithm
- Backward differentiation formula
- Error bound for the trapezoidal rule
- Bicubic interpolation
- Lagrange interpolation
- Spline interpolation
- Monotone cubic interpolation
- Divided differences
- Lagrange polynomial
- Barycentric interpolation formula
- Runge's phenomenon
- Bilinear interpolation
Further reading
About this page
| Tag | SS1YMS2NPC |
|---|---|
| URI | m2://SS1YMS2NPC |
| Kind | concept |
| Writing | W0 stub |
| MSC | 41A05, 65D05 |
| Same as |
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Used by
- Newton polynomial
- Birkhoff interpolation
- Mean value theorem for divided differences
- Multivariate interpolation
- Direct collocation
- Hermite interpolation
- Muller's method
- Interpolation error formula
- Neville's algorithm
- Backward differentiation formula
- Bicubic interpolation
- Lagrange interpolation
- Spline interpolation
- Monotone cubic interpolation
- Divided differences
- Lagrange polynomial
- Barycentric interpolation formula
- Bilinear interpolation