> On 28 Dec 2017, at 13:08 , Kurt Hornik <kurt.hor...@wu.ac.at> wrote: > >>>>>> Jan Motl writes: > >> The chisq.test on line 57 contains following code: >> STATISTIC <- sum(sort((x - E)^2/E, decreasing = TRUE)) > > The preceding 2 lines seem relevant: > > ## Sorting before summing may look strange, but seems to be > ## a sensible way to deal with rounding issues (PR#3486): > STATISTIC <- sum(sort((x - E) ^ 2 / E, decreasing = TRUE)) > > -k
My thoughts too. PR 3486 is about simulated tables that theoretically have STATISTIC equal to the one observed, but come out slightly different, messing up the simulated p value. The sort is not actually intended to squeeze the very last bit of accuracy out of the computation, just to make sure that the round-off affects equivalent tables in the same way. "Fixing" the code may therefore unfix PR#3486; at the very least some care is required if this is modified. -pd > >> However, based on book "Accuracy and stability of numerical algorithms" >> available from: >> >> http://ftp.demec.ufpr.br/CFD/bibliografia/Higham_2002_Accuracy%20and%20Stability%20of%20Numerical%20Algorithms.pdf >> Table 4.1 on page 89, it is better to sort the data in increasing order than >> in decreasing order, when the data are non-negative. > >> An example: >> x = matrix(c(rep(1.1, 10000)), 10^16, nrow = 10001, ncol = 1) # We >> have a vector with 10000*1.1 and 1*10^16 >> c(sum(sort(x, decreasing = TRUE)), sum(sort(x, decreasing = FALSE))) >> The result: >> 10000000000010996 10000000000011000 >> When we sort the data in the increasing order, we get the correct result. If >> we sort the data in the decreasing order, we get a result that is off by 4. > >> Shouldn't the sort be in the increasing order rather than in the decreasing >> order? > >> Best regards, >> Jan Motl > > >> PS: This post is based on discussion on >> https://stackoverflow.com/questions/47847295/why-does-chisq-test-sort-data-in-descending-order-before-summation >> and the response from the post to r-h...@r-project.org. >> ______________________________________________ >> R-devel@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-devel > > ______________________________________________ > R-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Office: A 4.23 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
