Omega vs Deltax, for the parameters alpha=0.05 beta=1.5, with the new generalized omega

>> clear
>> load datos_celegans_struct
>> [pos,omega_general,costes,x]=coste2pos_restofijas(todas.A*.05,todas.M*1.5+todas.S,todas.f,todas.pos_real,1);
>> desv=abs(todas.pos_real-pos);
>> plot(desv,omega_general,’.’)

To start with, only one outlier. Note that the new omega depends on the exponent, so this by itself favors exponent 1.

Bad news for the fit to the mean (without the outlier):

>> buenas=(desv<.2 | omega_general<20);
>> sum(~buenas)
ans =
1
>> [xi,b]=omegadesv2bestfittingexponent_exp(desv(buenas),omega_general(buenas))
xi =
4.5068
b =
0.1092

And of course, again great news for the fit to the envelope (again, without the outlier):

>> [desv_acum,omega_media]=omegadesv_acumuladas(desv(buenas),omega_general(buenas),1,4);

>> plot(log10(desv_acum),log10(omega_media),’.-‘)

I am starting to believe the theory about Bayes being especially affected by the most deviated ones, and the envelope getting that.

 

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2 Responses to “Omega vs Deltax, for the parameters alpha=0.05 beta=1.5, with the new generalized omega”

  1. gonzalopolavieja Says:

    Good theory that one…:)
    Question:Is there something special about the prob we get from bayes that makes the mean particularly sensitive to amount of data orparticularly insensitive to omega?

  2. gonzalopolavieja Says:

    Si tuvieses tiempo: ver como cambia la media y la envolvente con el numero de pasos en simulated annealing.
    Sepuede pintar el valor del exponenente del fit en el tiempo, paramedia y envolvente.


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