- #1
Amanheis
- 67
- 0
I need to quantify the statistical significance of how much a model deviates from a given set of data points, and I cannot do a fit.
Let's say the model is a one-parameter description of some time dependent quantity f_a(t). I have data points at n different times including error bars, so pi = {ti, fa(ti), sigmai}. The reason I cannot do a fit is that the data is actually the predicted errors for some fiducial value a_0, and the fit would obviously just find a = a0.
I want to know how far off a couple models with either a = a1 or a = a2 are. So in other words, how well does fa1(t) fit the data points pi? Can I rule it out on some confidence level?
It seems difficult to express my problem, I hope it became clear enough. All I am asking for is a hint in the right direction, so if you know some relevant reference, I can just get it in the library. I already calculated the likelihood L(a) but don't really know how to proceed.
Thanks.
Let's say the model is a one-parameter description of some time dependent quantity f_a(t). I have data points at n different times including error bars, so pi = {ti, fa(ti), sigmai}. The reason I cannot do a fit is that the data is actually the predicted errors for some fiducial value a_0, and the fit would obviously just find a = a0.
I want to know how far off a couple models with either a = a1 or a = a2 are. So in other words, how well does fa1(t) fit the data points pi? Can I rule it out on some confidence level?
It seems difficult to express my problem, I hope it became clear enough. All I am asking for is a hint in the right direction, so if you know some relevant reference, I can just get it in the library. I already calculated the likelihood L(a) but don't really know how to proceed.
Thanks.