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README.md	README.md
aitkens_method.py	aitkens_method.py
bisection_method.py	bisection_method.py
fixed_point.py	fixed_point.py
muellers_method.py	muellers_method.py
newton_raphson.py	newton_raphson.py
secant_method.py	secant_method.py
steffensens_method.py	steffensens_method.py

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Numerical Analysis Package

Finding the roots of a polynomial:
- Bisection Method: Used to find the roots of a polynomial. Guaranteed to converge.
- Fixed Point Iteration: x = g(x)
- Newton-Raphson: The fastest converging method, with an order of 2. Need extra computation for the derivative and might fail when f'(x) = 0
- Secant Method: Uses the same methodology of Newton's method, but without the need of calculating the derivative. Needs two point for manual slope calculation.
- Müeller's Method: Faster than Secant method, slower than Newton's. The benefit of using this method is that it can find Complex Roots without the need of a derivative. But in order to do so, we need to have an idea of the curve on which our root lies and needs three points so it can plot a parabola passing through it.
Accelerating techniques:
- Aitken's Method: His method speeds up the convergence of any of the above methods by calculating 𝝙 after we have 3 points.
- Steffensen's Method: A combination of Fixed-Point Iteration and the accelration of Aitken's Method. Compute three points using Fixed-Point and apply Aitken's on those three to get another point. Then again perform Fixed-Point Iteration on it and profit.

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