![]() ![]() William Jeremy Artman, Ashkan Ertefaie, Kevin G Lynch, James R McKay, and Brent A Johnson MininĪ Marginal Structural Model for Partial Compliance in SMARTs ![]() Mingwei Tang, Gytis Dudas, Trevor Bedford, and Vladimir N. Papers to Appear in Subsequent Issues Fitting stochastic epidemic models to gene genealogies using linear noise approximation I'm glad I had a look at all of them.Click “ published issues” to see more. Every single one of them had something most of the others lacked. When I did nonparametrics as an undergrad, there were something like eight books in the recommended reading, perhaps more. Read through a few of them and find several you like. ![]() I'd start with a university library and browse around on searches with terms like in the above titles, and if possible, see what's nearby. There are dozens of good books, some older than the three I mentioned, some newer some may well suit you better than any I've mentioned. If you can find it it's a good introduction a worthwhile one to pick up second hand if you don't buy it new. Nowadays the code in it looks somewhat dated, but on the other hand, it's generally readable enough to translate. ![]() I found Neave and Worthington's " Distribution-Free tests" very readable when it first came out (and in many ways it still is). I'd strongly suggest starting with books, and reading more than one book.Ĭonover's " Practical Nonparametric Statistics" is good, and one I'd definitely lean toward including in any list.ĭaniel's " Applied Nonparametric statistics" is very good, reasonably comprehensive for its size. It depends on what you mean by 'concise', what kind of level of treatment you're seeking (including mathematical vs concepts and intuition), what techniques you want included. ![]()
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