Joshua, thanks for your reply. I have tried out the following scaling and it seems to work fine:
scaledVariable <- (test-min(test)+0.001)/(max(test)-min(test)+0.002) The gamma distribution parameters are obtained using the scaled variable and samples obtained from this distributions are scaled back using: scaled <- (randomSamples*(max(test) - min(test) + 0.002)) + min(test) - 0.001 Is there a better way to scale the variable??? I would prefer fitting a distribution without scaling it. Thank you. Ravi -- View this message in context: http://r.789695.n4.nabble.com/Fitting-gamma-and-exponential-Distributions-with-fitdist-tp3477391p3480265.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.
