Hang on, now I'm very confused. What is the information you have collected? Is it x and y? k and x? which one is the count?
John Sanders-2 wrote: > > 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 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. > > -- View this message in context: http://www.nabble.com/fitting-a-truncated-power-law-tp24798791p24819260.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
