Hello folks:
I am facing a small confusion that I have not been able to resolve. I
am trying to fit a beta geometric distribution to my dataset. I tried
the standard chi square goodness of fit test and this is rejected in
my data. (chi square = 122 and df = 34).
However an examination of the correlation between the two series shows
a correlation of .9995 and I actually tried superimposing a plot of
the observed and the expected values. The values are extremely close.
I tried something that may not be entirely right in this context but
just out of curiosity. I used the kolmogorov-Smirnov test by treating
the observed and the expected values as different groups and the test
indicated that the distributions were not different between the
observed and the expected values .
Two-sample Kolmogorov-Smirnov test for equality of distribution functions:
Smaller group D P-value Exact
----------------------------------------------
0: 0.2059 0.237
1: -0.0882 0.767
Combined K-S: 0.2059 0.467 0.307
Can someone suggest a way forward. Is it correct to assume that the
model fits the data ?
Thanks
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