# Parameter estimation in mathematical models of common functions (sine, cos, exp and other special functions)

**URL:** https://discourse.julialang.org/t/parameter-estimation-in-mathematical-models-of-common-functions-sine-cos-exp-and-other-special-functions/130325
**Category:** New to Julia
**Tags:** package, physics, curve-fitting
**Created:** [June 30, 2025, 8:36am UTC](https://discourse.julialang.org/t/parameter-estimation-in-mathematical-models-of-common-functions-sine-cos-exp-and-other-special-functions/130325 "2025-06-30T08:36:27Z")
**Posts on this page:** 1
**Showing post:** 4

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### Author: ![Tamas\_Papp](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/tamas_papp/32/25949_2.png) [@Tamas\_Papp](https://discourse.julialang.org/u/Tamas_Papp)
#### Post date: [June 30, 2025, 11:43am UTC](https://discourse.julialang.org/t/parameter-estimation-in-mathematical-models-of-common-functions-sine-cos-exp-and-other-special-functions/130325/4 "2025-06-30T11:43:40Z")

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> [@Geegee](#):
>
> Our code leverages things like FFT, convolution, smoothing with gaussian filters and  
> a lot of heuristics to get to a decent parameter estimation (far from perfect).

You can probably find all of these ingredients in the Julia ecosystem, but your description above should answer

> [@Geegee](#):
>
> why there isn’t a package for this out there

: because you need to make a lot of decisions like this, so there is no general _method_ for “estimation”.

That said, I am not sure why something simple like minimizing a sum of squared discrepancies would not work, but maybe your problem domain has something special.

If you want to get more specific help, post an MWE for generating the data, and the questions you have.

> [@Please read: make it easier to help you](https://discourse.julialang.org/t/please-read-make-it-easier-to-help-you/14757):
>
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