Brian, It is hard to say at this level of resolution of the question, but it would seem that you might be able to start by considering each sample vector as as repeated measurement of the fiber length -- so 12 obs in the first 1/16th bin, 235 in the next and so forth, all associated with some vector of covariates representing location, variety, etc, then the conventional quantile regression would serve to estimate a conditional quantile function for fiber length for each possible covariate setting --- obviously this would require some model for the way that the covariate effects fit together, linearity, possible interactions, etc etc, and it would also presume that it made sense to treat the vector of responses as independent measurements. Building in possible dependence involves some new challenges, but there is some recent experience with inferential methods for microarrays that have incorporated these effects.
I'd be happy to hear more about the data and possible models, but this should be routed privately since the topic is rather too specialized for R-help. url: www.econ.uiuc.edu/~roger Roger Koenker email [EMAIL PROTECTED] Department of Economics vox: 217-333-4558 University of Illinois fax: 217-244-6678 Champaign, IL 61820 On Oct 26, 2006, at 7:20 AM, Brian Gardunia wrote: > I am relatively new to R, but am intrigued by its flexibility. I > am interested in quantile regression and quantile estimation as > regards to cotton fiber length distributions. The length > distribution affects spinning and weaving properties, so it is > desirable to select for certain distribution types. The AFIS fiber > testing machinery outputs a vector for each sample of type c(12, > 235, 355, . . . n) with the number of fibers in n=40 1/16 inch > length categories. My question is what would be the best way to > convert the raw output to quantiles and whether it would be > appropriate to use quantile regression to look at whether location, > variety, replication, etc. modify the length distribution. > > ______________________________________________ > [email protected] 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. ______________________________________________ [email protected] 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.
