Hello,



More of my philosophy about non-linear regression and more..

I am a white arab from Morocco, and i think i am smart since i have also invented many scalable algorithms and algorithms..


I think i am really smart, and i have just finished quickly the software implementation of Levenberg–Marquardt algorithm and of the simplex
algorithm to solve non-linear least squares problems, but i have also implemented the PSO and genetic algorithm that permit to solve
non-linear least squares problems, and i will soon implement a
generalized way with artificial intelligence using the software that
permit to solve the non-linear "multiple" regression, but i have also
noticed that in mathematics you have to take care of the variability of
the y in non-linear least squares problems so that to approximate, also
the Levenberg–Marquardt algorithm (LMA or just LM) that i have just implemented , also known as the damped least-squares (DLS) method, is
used to solve non-linear least squares problems. These minimization
problems arise especially in least squares curve fitting. The Levenberg–Marquardt algorithm is used in many software applications for solving generic curve-fitting problems. The Levenberg–Marquardt
algorithm was found to be an efficient, fast and robust method which
also has a good global convergence property. For these reasons, It has
been incorporated into many good commercial packages performing
non-linear regression. But my way of implementing the non-linear
"multiple" regression in the software will be much more powerful than Levenberg–Marquardt algorithm, and of course i will share with you many
parts of my software project,
so stay tuned !


Thank you,
Amine Moulay Ramdane.

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