What software for optimization surface of 4 parameters?

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Discussion Overview

The discussion revolves around the optimization of a function based on four parameters, focusing on finding a stable maximum from a dataset containing 60,000 values. Participants explore different software tools and optimization methods suitable for this task, particularly comparing Matlab and R.

Discussion Character

  • Exploratory, Technical explanation, Debate/contested

Main Points Raised

  • One participant inquires about the best software for optimizing a function with four parameters, expressing familiarity with Matlab and some knowledge of R.
  • Another participant suggests using R, particularly highlighting the Nelder-Mead optimization method as a potentially suitable approach for the dataset size.
  • A later reply emphasizes that the Nelder-Mead algorithm does not require an explicit form of the function, only the function values, and mentions that it is also known as the "simplex" method.
  • There is a challenge regarding the applicability of the Nelder-Mead method due to the lack of an explicit function, which raises questions about the method's suitability.
  • References to additional resources, including the neldermead package in R and literature on optimization methods, are provided by participants.

Areas of Agreement / Disagreement

Participants express differing views on the applicability of the Nelder-Mead method, with some asserting it can be used without an explicit function while others question its feasibility under those conditions. The discussion remains unresolved regarding the best approach to take.

Contextual Notes

There is uncertainty about the requirements for the Nelder-Mead method and whether it can be effectively applied without an explicit function. Participants also have varying levels of experience with the suggested software tools.

Tosh5457
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Hello,

I have data for optimization that contains different values of 4 different parameters, and the respective function value based on them. I want to find the maximum of this function, while making sure it's a "stable" maximum, i.e., for nearby parameters, the value of the function shouldn't change that much. My only question is what tool to use for this, since I have 60k values in total? I have experience in Matlab, can that be done in a reasonable amount of time there? I also have some basic knowledge of R, and can learn fast anyway, is this more suitable to do in R?

Thanks!
 
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Tosh5457 said:
Hello,

I have data for optimization that contains different values of 4 different parameters, and the respective function value based on them. I want to find the maximum of this function, while making sure it's a "stable" maximum, i.e., for nearby parameters, the value of the function shouldn't change that much. My only question is what tool to use for this, since I have 60k values in total? I have experience in Matlab, can that be done in a reasonable amount of time there? I also have some basic knowledge of R, and can learn fast anyway, is this more suitable to do in R?

Thanks!

I would definitely go with R, even (or I should say especially) with 60,000 values. Also, but depending on the context, I think the Nelder-Mead optimization method would be an interesting approach to try.

I've used the neldermead package before and it served me well.

More information here : https://cran.r-project.org/web/packages/neldermead/neldermead.pdf
 
h6ss said:
I would definitely go with R, even (or I should say especially) with 60,000 values. Also, but depending on the context, I think the Nelder-Mead optimization method would be an interesting approach to try.

I've used the neldermead package before and it served me well.

More information here : https://cran.r-project.org/web/packages/neldermead/neldermead.pdf


Thank you, will definitely look into that method in R.
 
Ok, Nelder-mead won't work, because I don't have the function explicitly...
 
Tosh5457 said:
Ok, Nelder-mead won't work, because I don't have the function explicitly...
The explicit form of the function is not necessary. The Nelder-Mead algorithm only requires function values.

The algorithm is often called the "simplex" method, maybe you can find more information about it under that label. Also, many books cover the subject, e.g. Richard Brent's book Algorithms for Minimization Without Derivatives.
 

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