Newton's Method: Checking that ff'' >0 - Why and What if Not?

In summary, when using Newton's method to find roots, it is important to check that f f'' >0. This condition ensures that the sequence will monotonically converge to the root. However, if this condition is not met, the method may still converge linearly or not converge at all depending on the other conditions. It is also worth noting that the f'\neq 0, f'' finite conditions are weaker than the f f'' >0 condition, but they guarantee quadratic convergence.
  • #1
tysonk
33
0
When using Newton's method to find roots, why should we check that ff'' >0 . I can't find an adequate reason for this. Does Newton's method fail otherwise? If so why? Thanks.
 
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  • #2
You should check out the discussion at http://en.wikipedia.org/wiki/Newton's_method#Analysis The method doesn't necessarily fail, but f f'' >0 is a condition that the sequence monotonically converges to the root. If you read on a bit further into the next section on that page, they explain that [tex]f'\neq 0[/tex], [tex]f''[/tex] finite are conditions for quadratic convergence. These latter conditions are much weaker than the f f'' >0 condition.
 
  • #3
Oh so if that condition is not met, it converges linearly?
 
  • #4
tysonk said:
Oh so if that condition is not met, it converges linearly?

No, there's no reason to conclude that. If you want to understand the [tex]f'\neq 0[/tex], [tex] f~ f''>0[/tex], you might want to consider a few sketches of the behavior of the function to the right of a root. You'll see how that condition leads to the sequence being monotone decreasing.

If the other set of conditions, [tex]f'\neq 0[/tex], [tex]f''[/tex] finite, is not met, it's possible that the sequence does not converge at all.
 

Related to Newton's Method: Checking that ff'' >0 - Why and What if Not?

1. What is Newton's Method?

Newton's Method is an iterative algorithm used to find the roots of a polynomial function. It involves using an initial guess and repeatedly applying a formula to refine the guess until the desired accuracy is achieved.

2. How does Newton's Method work?

Newton's Method uses the slope of the tangent line at a given point on the graph of a function to approximate the root of the function. The formula for Newton's Method is xn+1 = xn - f(xn)/f'(xn), where f(x) is the function and f'(x) is its derivative.

3. Why is it important to check that ff'' > 0 in Newton's Method?

Checking that ff'' > 0 ensures that the function is convex at the point of approximation. This guarantees that the next iteration will be closer to the actual root and prevents the algorithm from getting stuck at a local maximum or minimum.

4. What happens if ff'' < 0 in Newton's Method?

If ff'' < 0, then the function is concave at the point of approximation. This means that the next iteration may actually move further away from the root instead of getting closer to it. This can result in the algorithm not converging to the actual root or converging very slowly.

5. Can Newton's Method be used for any function?

No, Newton's Method can only be used for functions that are continuous and have a continuous derivative. It also requires an initial guess that is reasonably close to the actual root. If the function is not well-behaved or the initial guess is too far from the root, the algorithm may not converge or may converge to the wrong root.

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