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.
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