Dear Glen_b,
The function I'm trying to fit has the form: P(k) ~ k^(-y) exp (– k ⁄ kx) And deals with count data. I'm a newbie, so any more specific suggestion would be greatly appreciated. john John Sanders-2 wrote: > > How can I fit a truncated power law to a vector? I can't find a function > to do that. If the function provides an AIC, even better. > Okay, "power law" I understand - f(x) = k.x^a, or on the log-scale log(f(x)) = log(k) + a log(x) (linear) I was unfamiliar with the term "truncated power law", but after looking on the internet I see that the term implies what appears to be replacing the linear fit with a linear spline fit to log(y) in terms of log(x) - but the usual application seems to be to fit probability distribution to count data; in this case you fit essentially a two-part Pareto distribution (or Zipf if the variable is discrete) - again the log-fitted-density is like a linear spline in the logs. Is the vector of data you have counts to which you wish to fit a distribution, or is it a set of measurements? If I understand the problem correctly, I think it could probably be done using linear splines with GLMs, which can be done in a couple of packages. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
