Metric for linear and 0.5 cases

If I try to compute more tan 10^7 permutations, Matlab runs out of memory. This can be solved, by saving the results in files as they are computed. But for now, I post results for 10^7 permutations (run in remotón).

Calculations for alfa, beta of our pnas, exponent 1:

pos_opt=coste2pos_num_ruido(todas.A*.05,todas.M*1.5+todas.S,todas.f,1,0);
[m,coste_real,coste_perm]=metrica_pot(todas.A*.05,todas.M*1.5+todas.S,todas.f,todas.pos_real,1,10^7,pos_opt,4);
hist(coste_perm,100)
>> hold on
>> ejes=axis;
>> plot(coste_real*[1 1],ejes(3:4),’k’)
>> save metrica_alfabetapnas_lineal m coste_perm coste_real

m is 0, no permutation has lower cost than the real case. So p<10^-7.

Calculations for alfa and beta predicted by Bayes, and exponent 0.5:

>> [m,coste_real,coste_perm]=metrica_pot(todas.A*10^-1.1,todas.M*10^-.9+todas.S,todas.f,todas.pos_real,0.5,10^7,datos.pos_opt,4);
>> cd ..
>> cd metricaelegans
>> save metrica_alfabetabayes_cerocinco m coste_perm coste_real
>> m
m =
0
>> close all
>> hist(coste_perm,100)
>> hold on
>> ejes=axis;
>> plot(coste_real*[1 1],ejes(3:4),’k’)

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New Figure 3 (Bayes) for the paper

Feb 25, 2009

fig_pap_bayes_02(1,zeros(100))

Tests of different deformations of the colormap (changing variable exponent in the program):

>> fig_pap_bayes_02(1,zeros(100))

Normal colormap:

Deformed with the square root:

Deformed with x^.2

Current version, and calculation of expected values and standard deviations for alfa, beta and the exponent:

>> fig_pap_bayes_02(1,zeros(100))
expectedvalue_pot =
0.4885
sd_pot =
0.0662
expectedvalue_logalfa =
-1.1067
sd_logalfa =
0.0887
expectedvalue_logbeta =
-0.9375
sd_logbeta =
0.1261

Feb 26, 2009

>> fig_pap_bayes_03(1,zeros(100))
expectedvalue_pot =
0.4885
sd_pot =
0.0662
expectedvalue_logalfa =
-1.1067
sd_logalfa =
0.0887
expectedvalue_logbeta =
-0.9375
sd_logbeta =
0.1261

New figure 1 for the paper

New name for the generator file: fig_pap_presentacion_01.m (old name was fig_pap_presentaelegans_05.m)

 

 

Another version, with a line in box a. I do not like it as it is, but maybe we can include something similar to clarify that the red dot is in the optimum?

fig_pap_presentacion_02(1,zeros(100))