Dependence of the slope on R, Q and the fitting radius

>> pendientes=simul_pendientes(6000:250:8500,-.5:.2:1,200);
>> R=6000:250:8500;
>> Q=-.5:.2:1;
>> imagesc(Q,R,pendientes); set(gca,’YDir’,’normal’)

>> mesh(Q,R,pendientes)

So approximately linear change with R, and almost no change with Q.

Dependence on the fitting radius:

Now we see the dependence with the fitting area:
>> [pendientes_radioaj,p_radioaj]=simul_pendientes_radioajuste(8000,.7,1000:200:3000,100);
>> p_radioaj’
ans =
1.0e-005 *
0.0000 0.1023 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

All very significant.

>> radiosaj=1000:200:3000;
>> plot(radiosaj,pendientes_radioaj)

>> save pendientes pendientes R Q pendientes_radioaj radiosaj

Also a big change, depending on the fitting radius.

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Effect of having different dispersion in the center and in the periphery

We do not see a significant widening of the pattern. However, a very relevant bias appears:

Simulations with std 10 in the central 1.5 mm (radius), and std 20 in the rest (up to 3 mm radius):

>> fig_pap_simulaciones_ruidoperiferia_01(5,1)

Simulations with std 10 in the central 1.5 mm (radius), and std 40 in the rest (up to 3 mm radius):

>> fig_pap_simulaciones_ruidoperiferia_01(5,1)