similar to: Question about Project: Posting list encoding improvements

On 20/09/2018 6:59 AM, Ralf Stubner wrote: > On 9/20/18 1:43 AM, Carl Boettiger wrote: >> For a well-tested C algorithm, based on my reading of Lemire, the unbiased >> "algorithm 3" in https://arxiv.org/abs/1805.10941 is part already of the C >> standard library in OpenBSD and macOS (as arc4random_uniform), and in the >> GNU standard library. Lemire also

Hello, Top posting. Several people have asked about the code to replicate my results. I have cleaned up the code to remove an x/y coordinate bias for displaying the results directly on a 640 x 480 VGA adapter. You can find the code here: http://people.redhat.com/sgrubb/files/vseq.c To collect R samples: X <- runif(10000, min = 0, max = 65535) write.table(X, file =

On 9/20/18 1:43 AM, Carl Boettiger wrote: > For a well-tested C algorithm, based on my reading of Lemire, the unbiased > "algorithm 3" in https://arxiv.org/abs/1805.10941 is part already of the C > standard library in OpenBSD and macOS (as arc4random_uniform), and in the > GNU standard library. Lemire also provides C++ code in the appendix of his > piece for both this and

Hello, On Thursday, September 20, 2018 11:15:04 AM EDT Duncan Murdoch wrote: > On 20/09/2018 6:59 AM, Ralf Stubner wrote: > > On 9/20/18 1:43 AM, Carl Boettiger wrote: > >> For a well-tested C algorithm, based on my reading of Lemire, the > >> unbiased "algorithm 3" in https://arxiv.org/abs/1805.10941 is part > >> already of the C standard library in

Not sure what should happen theoretically for the code in vseq.c, but I see the same pattern with the R generators I tried (default, Super-Duper, and L'Ecuyer) and with with bash $RANDOM using N <- 10000 X1 <- replicate(N, as.integer(system("bash -c 'echo $RANDOM'", intern = TRUE))) X2 <- replicate(N, as.integer(system("bash -c 'echo $RANDOM'",

On 9/20/18 5:15 PM, Duncan Murdoch wrote: > On 20/09/2018 6:59 AM, Ralf Stubner wrote: >> It is difficult to do this in a package, since R does not provide access >> to the random bits generated by the RNG. Only a float in (0,1) is >> available via unif_rand(). > > I believe it is safe to multiply the unif_rand() value by 2^32, and take > the whole number part as an

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =

Hi, I think that it would be a good thing to know more about those 2 projects (and also the future patent free format). I think that many people as me know about Lame, but not about Vorbis, and vice-versa. It would be fine that someone (perhaps the maintainer) of every project would introduce to both group of people those projects. 2 things would be interesting (to my mind): - to know about the

For a well-tested C algorithm, based on my reading of Lemire, the unbiased "algorithm 3" in https://arxiv.org/abs/1805.10941 is part already of the C standard library in OpenBSD and macOS (as arc4random_uniform), and in the GNU standard library. Lemire also provides C++ code in the appendix of his piece for both this and the faster "nearly divisionless" algorithm. It would be

Hello list, I wonder if anyone might be able to help me troubleshoot an attempt at porting some simple Python code to R. The function below is supposed to take a matrix containing item ratings from various users and, given a vector containing at least 1 rating and 1 missing value, employ a 'weighted slope one' algorithm to predict the missing values. The algorithm itself is fairly

Dear, When fitting the following model knots <- 5 lrm.NDWI <- lrm(m.arson ~ rcs(NDWI,knots) I obtain the following result: Logistic Regression Model lrm(formula = m.arson ~ rcs(NDWI, knots)) Frequencies of Responses 0 1 666 35 Obs Max Deriv Model L.R. d.f. P C Dxy Gamma Tau-a R2 Brier 701 5e-07 34.49

I'm trying to integrate a Linux machine into our Win2K3 ADS-based network. The machine must primarily serve as a user workstation (i.e., a Samba Client), although it also needs to serve at least one share for backup purposes. I'd like to emulate the behavior of our WinXP machines in that any user in our small company can login to any computer in the domain based on network

Dear List, i am trying to produce a 3d plot using wireframe using the code: wireframe(Residuals_FD ~ Elevation * Temperature, data = data2, scales = list(arrows = FALSE), drape = TRUE, colorkey = TRUE) As you can see when the code (using the data below) is run the plot area is set-up correctly but the actual surface is missing? Any help would be greatly appreciated. Chris #data Elevation

I did some additional testing - I stopped Kafka on the host, and kicked off a disk check, and it ran at the expected speed overnight. I started kafka this morning, and the raid check's speed immediately dropped down to ~2000K/Sec. I then enabled the write-back cache on the drives (hdparm -W1 /dev/sd*). The raid check is now running between 100000K/Sec and 200000K/Sec, and has been for several

rucker222 wrote: > The drop down layer selection menu at the top left of the screen directly above where the drawing 1 tab is opens upwards off of the screen once the drawing has a few layers on it. jjmckenzie wrote: > Log file please. I loaded a drawing with plenty of layers and then clicked on the layer drop down menu a couple of times before exiting ProgeCAD. Log file below. (sorry

I tried the code that Richard O'Keefe posted last week, to wit: library(chron) ymd.to.POSIXlt <- function (y, m, d) as.POSIXlt(chron(julian(y=y, x=m, d=d))) n <- 100000 y <- sample(1970:2004, n, replace=TRUE) m <- sample(1:12, n, replace=TRUE) d <- sample(1:28, n, replace=TRUE) system.time(ymd.to.POSIXlt(y, m, d)) [1] 8.78 0.10

A quick point of order here: arguing with Duncan in this forum is helpful to expose ideas, but probably neither side will convince the other; eventually, if you want this adopted in core R, you'll need to convince an R-core member to pursue this fix. In the meantime, a good, well-tested implementation in a user-contributed package (presumably written in C for speed) would be enormously

All of our Kafka clusters are fairly write-heavy. The cluster in question is our second-heaviest ? we haven?t yet upgraded the heaviest, due to the issues we?ve been experiencing in this one. Here is an iostat example from a host within the same cluster, but without the RAID check running: [root at r2k1 ~] # iostat -xdmc 1 10 Linux 3.10.0-327.13.1.el7.x86_64 (r2k1) 05/27/16 _x86_64_ (32 CPU)

Hello folks, TL;DR: This is my proposed hashing interface based on a proposed standard hashing interface. It also is implemented with a much faster and higher quality algorithm than the current one. This is an *early draft* of the code, looking for initial feedback. There has been recent interest in improving the quality and consistency of LLVM's approach to hashing. In particular, getting

flight 17325 linux-linus real [real] http://www.chiark.greenend.org.uk/~xensrcts/logs/17325/ Regressions :-( Tests which did not succeed and are blocking, including tests which could not be run: test-amd64-amd64-xl 9 guest-start fail REGR. vs. 12557 test-amd64-i386-xl-credit2 15 guest-stop fail REGR. vs. 12557 test-amd64-i386-xl 15 guest-stop