indie452
Nov24-11, 05:54 AM
hi
i have some data (star counts) and i have a model and i want to perform min chi squared
so if i call my data di, and my model mi with std dev = \sigmai = 1
then \chi^2 = \sum \frac{(di - mi)^2}{\sigma i^2}
no my model is this mi = bi - Fo where bi is the background which has been assumed to be 5, and Fo is some constant flux. from this i am thus assuming that the data is ecpected to be a flat line.
Now i want to determine the min ch squared estimate for Fo, but i am not sure how.
I have gotten this far:
\frac{d\chi ^2}{dFo} = -2\sum \frac{(di - bi - Fo)}{\sigma i^2} = 0
any help is appreciated thanks
i have some data (star counts) and i have a model and i want to perform min chi squared
so if i call my data di, and my model mi with std dev = \sigmai = 1
then \chi^2 = \sum \frac{(di - mi)^2}{\sigma i^2}
no my model is this mi = bi - Fo where bi is the background which has been assumed to be 5, and Fo is some constant flux. from this i am thus assuming that the data is ecpected to be a flat line.
Now i want to determine the min ch squared estimate for Fo, but i am not sure how.
I have gotten this far:
\frac{d\chi ^2}{dFo} = -2\sum \frac{(di - bi - Fo)}{\sigma i^2} = 0
any help is appreciated thanks