<<This page facilitates a collab on a possible paper "Inference for the uniform distribution">>
<<Michael wrote>>
I realize I owe you at least one paper, regarding random-to-fuzzy transformations on confidence structures post-propagation. What is happening with the paper about inference on the upper and lower bounds of a uniform distribution? Do I need to write something for that too?
<<Scott replied>>
Deferring to you, I didn't write up any text on the interference for min/max or mean/std for a uniform. I just decoded an email from you on the subject, implemented the code to do the inferences, compared them with various frequentist estimators, tested them with Singh plots, and explored some of their properties. See the https://sites.google.com/site/confidenceboxes/simulations/uniform-distribution. I suspect there is enough there for a paper. Comparing the c-boxes against the frequentist estimators--and probably some Bayesian for the sake of completeness--would be interesting. It might be nice to spring off of a recent paper (which I discussed on Need to add uniform to list of challenge problems and Comparing estimators) from the statistics teaching literature about the various frequentist estimators and how Bayes is soooo much better than them. Your original disquistion is at https://sites.google.com/site/confidenceboxes/say-1/c-boxforuniform.
<<to do>>
write an abstract for this paper
collate all the text and pictures from the links above onto this page
create pictures from the simulations (running code at first link in R)