Numerical Methods – When Does the Newton Raphson Method Fail?

approximationnewton raphsonnumerical methods

Can someone please tell me the conditions under which the Newton Raphson method will not converge?

I looked around online, and couldn't find a general way to determine convergence.

For example, for the Fixed Point iteration method, there is a simple way of determining: if we have $g(x_{n})=x_{n+1}$, then $|g'(x)|<1$ implies that the series $g$ will converge to its fixed point, but in the Newton Raphson method, It seems like it is totally depends on "luck", meaning if you were lucky enough to pick a "good" initial guess or not.

Best Answer

To visualize geometrically what's going on, I will code an interactive diagram with GNU Dr. Geo (free software of mine) from where I can drag the initial value (the red dot) and see how the method converge or not.

For example $x \rightarrow cos x + x$, comes with some mines, but not $x \rightarrow cos x +1.1x$.

When you get close to a flat area, the tangent sends you far away, even further than your initial value.

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Your best option is to get close to the root in an area without nul value of the derivative. I guess it is the tough part as it depends on the function. Visualizing can help.

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This article explains how to code with Pharo+DrGeo this interactive diagram and the link with the Hero method from the classical period.