Numerical Analysis - Finding the Rate of Convergence

AI Thread Summary
The discussion focuses on constructing code to determine the Asymptotic Error Constant and the order of convergence for iterative methods like Fixed Point, Newton-Raphson, and Secant using Scilab 4.0. The original poster is familiar with the theoretical orders but seeks assistance with coding for the asymptotic error constant applicable to any iteration. A response highlights that Scilab is now at version 6.0.2 and mentions relevant tutorials by openeering that could assist with the coding challenge. These tutorials, posted on January 14, 2015, are noted as useful resources for the topic. The conversation emphasizes the need for practical coding solutions in numerical analysis.
relinquished™
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Hello,

I'm trying to construct a code in determining the Asymptotic Error Constant and the order of the rate of convergence, r for several iterative methods like the Fixed point, Newton Rhapson, and Secant methods in determining roots, using Scilab 4.0 (which is said to behave much like MathLab, but I'm not that sure). I already know what their orders are, I just have a problem in determining the general code in determining the asymptotic error constant for ANY iteration. Any help is appreciated.

reli~
 
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Scilab is currently in version ##6.0.2##. As of now, there is this tutorial by openeering - a scilab professional partner, which is quite relevant to what is asked in the OP. Also, there are two more (relevant) tutorials besides the one already mentioned - all three posted on January 14, 2015, at openeering, here.
 

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