Refinement of the metric for the linear and 0.5 cases

See post on 25 Feb 09 for the calculations of permutations.

Linear case:

load metrica_alfabetapnas_lineal
>> m=aproximametrica(coste_real,coste_perm,1)
m =
6.7742e-012

 

Exponent 0.5:

>> load metrica_alfabetabayes_cerocinco
>> m=aproximametrica(coste_real,coste_perm,1)
m =
8.6886e-025

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Calibration of Bayes

fig_pap_calibracionbayesglobal_trocitos_01(1,0)

Works fine for most cases (except simulation 3). I will repeat that simulation with better binning. Anyway, simulations with xi=1 seem to work always well, so we can be still sure that xi<1.