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quickselectFS(w).m must call the mex by default. To do so, we need to change the gateway of the C functions compiled with mex.

Is your feature request related to a problem? Please describe.
parfor is compatible but the performance is not enhanced using the new 'local threads' parallel framework.

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Replace where possible parfor with parfeval to exploit the new 'local threads' parallel framework available since matlab 2020a.

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Desktop (please complete the following information):

• OS: [e.g. Windows or Mac]
• MATLAB version [e.g. 2019b]
• FSDA Version [e.g. 8.0.1]

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I noticed in the documentation for LXS https://github.com/UniprJRC/FSDA/blob/master/toolbox/regression/LXS.m that you use the old style of seeding for random number generation

randn('state', 123456);

This is a bad idea since it doesn't just seed the RNG, it actually changes the algorithm for random numbers generation to a very old one. Details at https://walkingrandomly.com/?p=2945

I suggest you do the following instead

rng(123456)

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Describe the solution you'd like
Faster code and faster parallel computing

es@Eds. /@Add.po [16^° Eπ>

In the ace.m file (FSDA -> toolbox -> regression -> ace.m) there's a missing explanation to line 258

%% ct vector containing the... ?

Follows issue #80:

• ensure syntactic consistency of calls to quickselectFS(w)
• replace calls to sort when only the order statistic is needed

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I'd suggest expanding Powertra.m to implement standardization (to mean=0 and std. dev. =1) after BoxCox or Yeo-Johnson is applied.

This would make Powertra.m equivalent to the scikit-learn PowerTransformer frequently used in Python DA workflows.