Hi,
I am using Cobaya to test a modified model in CAMB, with only two additional modification parameters varied, and all other parameters fixed. I chose some fiducial values for the two parameters, say A and B, to generate the mock DES data using the DES likelihood, and then fit the model to the data using DES likelihood only, with A and B varied. The result is OK with great convergence (quite small R-1), and the bestfit/mean values of the A and B are very close to my fiducials, also with smooth contour between A and B. However, for the chi2 stats from getdist, it gives something like:
Best fit sample -log(Like) = -1.831643
Ln(mean 1/like) = 1.779169
mean(-Ln(like)) = -0.828389
-Ln(mean like) = -1.151868
2*Var(Ln(like)) = 2.311052
which contains some negative values, and it is strange because the chi2 can never be negative. Also from the marge-stats file, the result for chi2 is like:
parameter mean sddev lower1 upper1 limit1 lower2 upper2 limit2
chi2* 2.0083858E+00 2.1499081E+00 -1.0033729E-02 2.4238994E+00 two -2.3517432E-01 6.1697150E+00 two \chi^2
so the negative chi2 might come from the large sdv compared to mean.
I searched the chi2 values in the chains but found no negative values in them, so I was wondering if this negativity issue comes from some kind of normalization process from getdsit? Are the results trustworthy in this case then? Thanks.
I am using Cobaya to test a modified model in CAMB, with only two additional modification parameters varied, and all other parameters fixed. I chose some fiducial values for the two parameters, say A and B, to generate the mock DES data using the DES likelihood, and then fit the model to the data using DES likelihood only, with A and B varied. The result is OK with great convergence (quite small R-1), and the bestfit/mean values of the A and B are very close to my fiducials, also with smooth contour between A and B. However, for the chi2 stats from getdist, it gives something like:
Best fit sample -log(Like) = -1.831643
Ln(mean 1/like) = 1.779169
mean(-Ln(like)) = -0.828389
-Ln(mean like) = -1.151868
2*Var(Ln(like)) = 2.311052
which contains some negative values, and it is strange because the chi2 can never be negative. Also from the marge-stats file, the result for chi2 is like:
parameter mean sddev lower1 upper1 limit1 lower2 upper2 limit2
chi2* 2.0083858E+00 2.1499081E+00 -1.0033729E-02 2.4238994E+00 two -2.3517432E-01 6.1697150E+00 two \chi^2
so the negative chi2 might come from the large sdv compared to mean.
I searched the chi2 values in the chains but found no negative values in them, so I was wondering if this negativity issue comes from some kind of normalization process from getdsit? Are the results trustworthy in this case then? Thanks.
Statistics: Posted by Zhuangfei Wang — March 22 2024