>>>>> Ravi Varadhan >>>>> on Thu, 26 Mar 2020 18:33:43 +0000 writes:
> This is also strange: > qbeta <- function (p, shape1, shape2, ncp = 0, lower.tail = TRUE, log.p = FALSE) > { > if (missing(ncp)) > .Call(C_qbeta, p, shape1, shape2, lower.tail, log.p) > else .Call(C_qnbeta, p, shape1, shape2, ncp, lower.tail, > log.p) > } > Since the default value is 0 for non-centrality, it seems like the logic above is wrong. When ncp=0, C_qnbeta would be called rather than C_qbeta. > Am I missing something? Yes. This has been on purpose (forever) and I think the help page mentions that - though probably a bit subtly. The way it is now, one can use both algorithms to compute what in principle should be the main thing. > Ravi > ________________________________ > From: R-devel <r-devel-boun...@r-project.org> on behalf of J C Nash <profjcn...@gmail.com> > Sent: Thursday, March 26, 2020 10:40:05 AM > To: Martin Maechler > Cc: r-devel@r-project.org > Subject: Re: [Rd] unstable corner of parameter space for qbeta? > Despite the need to focus on pbeta, I'm still willing to put in some effort. > But I find it really helps to have 2-3 others involved, since the questions back > and forth keep matters moving forward. Volunteers? > Thanks to Martin for detailed comments. > JN > On 2020-03-26 10:34 a.m., Martin Maechler wrote: >>>>>>> J C Nash >>>>>>> on Thu, 26 Mar 2020 09:29:53 -0400 writes: >> >> > Given that a number of us are housebound, it might be a good time to try to >> > improve the approximation. It's not an area where I have much expertise, but in >> > looking at the qbeta.c code I see a lot of root-finding, where I do have some >> > background. However, I'm very reluctant to work alone on this, and will ask >> > interested others to email off-list. If there are others, I'll report back. >> >> Hi John. >> Yes, qbeta() {in its "main branches"} does zero finding, but >> zero finding of pbeta(...) - p* and I tried to explain in my >> last e-mail that the real problem is that already pbeta() is not >> accurate enough in some unstable corners ... >> The order fixing should typically be >> 1) fix pbeta() >> 2) look at qbeta() which now may not even need a fix because its >> problems may have been entirely a consequence of pbeta()'s inaccuracies. >> And if there are cases where the qbeta() problems are not >> only pbeta's "fault", it is still true that the fixes that >> would still be needed crucially depend on the detailed >> working of the function whose zero(s) are sought, i.e., pbeta() >> >> > Ben: Do you have an idea of parameter region where approximation is poor? >> > I think that it would be smart to focus on that to start with. >> >> ---------------------------- >> >> Rmpfr matrix-/vector - products: >> >> > Martin: On a separate precision matter, did you get my query early in year about double >> > length accumulation of inner products of vectors in Rmpfr? R-help more or >> > less implied that Rmpfr does NOT use extra length. I've been using David >> > Smith's FM Fortran where the DOT_PRODUCT does use double length, but it >> > would be nice to have that in R. My attempts to find "easy" workarounds have >> > not been successful, but I'll admit that other things took precedence. >> >> Well, the current development version of 'Rmpfr' on R-forge now >> contains facilities to enlarge the precision of the computations >> by a factor 'fPrec' with default 'fPrec = 1'; >> notably, instead of x %*% y (where the `%*%` cannot have more >> than two arguments) does have a counterpart matmult(x,y, ....) >> which allows more arguments, namely 'fPrec', or directly 'precBits'; >> and of course there are crossprod() and tcrossprod() one should >> use when applicable and they also got the 'fPrec' and >> 'precBits' arguments. >> >> {The %*% etc precision increase still does not work optimally >> efficiency wise, as it simply increases the precision of all >> computations by just increasing the precision of x and y (the inputs)}. >> >> The whole Matrix and Matrix-vector arithmetic is still >> comparibly slow in Rmpfr .. mostly because I valued human time >> (mine!) much higher than computer time in its implementation. >> That's one reason I would never want to double the precision >> everywhere as it decreases speed even more, and often times >> unnecessarily: doubling the accuracy is basically "worst-case >> scenario" precaution >> >> Martin >> > ______________________________________________ > 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