Hi, I've got some data (picture at http://limnus.com/~ken/zipf.jpg ) that seems to very obviously follow a Zipf-Mandelbrot distribution, and I'm wondering how to best fit the parameters of the distribution given the data.
I'm using the equation y = P(x + A)^-B as the canonical form of the Zipf-Mandelbrot curve. As a first attempt, I fixed the two endpoints (x=1 and y=1) to coincide with the expected values on the graph, which analytically gives me values for P and B as functions of A. Then I twiddle around with values for A until it looks nice. On the attached graph, this means I end up with A=8. This method pretty clearly overfits the endpoints, and is subject to the whims of my eyeballs for A. What would members of this list suggest for alternative fitting methods? Thanks, -Ken _______________________________________________ R-lang mailing list [email protected] https://ling.ucsd.edu/mailman/listinfo.cgi/r-lang
