interpolation-approximation

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Function interpolation and approximation methods

General

What this skill does


# Interpolation and Approximation

## Purpose

Provides function interpolation and approximation methods for data fitting and function representation.

## Capabilities

- Polynomial interpolation (Lagrange, Newton, Chebyshev)
- Spline interpolation (cubic, B-spline)
- Rational approximation (Pade)
- Least squares fitting
- Minimax approximation (Remez algorithm)
- Approximation error bounds

## Usage Guidelines

1. **Method Selection**: Choose based on smoothness and accuracy needs
2. **Node Placement**: Use Chebyshev nodes to minimize Runge phenomenon
3. **Spline Order**: Select spline degree based on continuity requirements
4. **Error Analysis**: Bound approximation errors rigorously

## Tools/Libraries

- Chebfun
- scipy.interpolate

Files: 1

Size: 1.0 KB

Complexity: 8/100

Category: General

Source: https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/science/mathematics/skills/interpolation-approximation

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