Hi all,

I am trying to check if a supposedly purely power-law distribution of data
has in fact a break in it. Since this is a steep power-law, the data
towards the end of the spectrum is very few. What I am trying to see is if
the actual distribution is

y(x)= A x^(-a) 

or

y(x)= A x^(-a)   x < x_*
y(x)= A (x_*)^b x^(-a-b)  x > x_*

obviously if b=0 (or x_* is infinite), the second model reduces to the first
model.

So my question is, is this a model selection problem, or a parameter
estimation problem? Should I just start from the second model, and estimate
the parameter b from the data? Or should I be doing a model selection test,
and if the second model wins, then and only then try to estimate b and x_*?
Also, if I treat this as a parameter estimation problem, does the fact x_*
will be undetermined if b=0 (or close to 0) make the problem singular or
unsolvable?

Thanks,
rsina
.
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