similar to: faster base::sequence

Dear all, I would like to compute power of a square non symmetric matrix. This is a part of a simulation study. Matrices are quite large (e.g., 900 by 900), and contains many 0 (more than 99 %). I have try the function mtx.exp of the Biodem package: library(Biodem) m <- matrix(0, 900, 900) i <- sample(1:900, 3000, replace = T) j <- sample(1:900, 3000, replace = T) for(x in 1:3000)

Dear wise ones, I have a problem assigning different colors to bars in a barplot. The data I'm using is the following dataframe (truncated) : > L0 r n p t [...] 18 19 1 1 RFM 19 20 1 1 RFM 20 21 2 1 RFM 21 23 6 1 RIH 22 24 2 1 ROC 23 25 1 1 ROC 24 26 1 1 ROC 25 27 2 1 ROC 26 28 2 1 RFT 27 29 1 1 RFT 28 30 2 1 RFT 29 31 1 1 ROH [...] My barplot should

> -----Original Message----- > From: linux-pci-owner at vger.kernel.org [mailto:linux-pci-owner at vger.kernel.org] > On Behalf Of Yijing Wang > Sent: Saturday, July 26, 2014 8:39 AM > To: linux-kernel at vger.kernel.org > Cc: Xinwei Hu; Wuyun; Bjorn Helgaas; linux-pci at vger.kernel.org; > Paul.Mundt at huawei.com; James E.J. Bottomley; Marc Zyngier; linux-arm- > kernel at

> -----Original Message----- > From: linux-pci-owner at vger.kernel.org [mailto:linux-pci-owner at vger.kernel.org] > On Behalf Of Yijing Wang > Sent: Saturday, July 26, 2014 8:39 AM > To: linux-kernel at vger.kernel.org > Cc: Xinwei Hu; Wuyun; Bjorn Helgaas; linux-pci at vger.kernel.org; > Paul.Mundt at huawei.com; James E.J. Bottomley; Marc Zyngier; linux-arm- > kernel at

I evaluated the Bayes factor in the k=2 allele case with a "triangular" prior under the null as in the example in the help file: HWETriangBF2(nvec=c(88,10,2)) [1] 0.4580336 When I swap the n11 entry and n22 entry of nvec, I received totally different Bayes factor: > > HWETriangBF2(nvec=c(2,10,88)) [1] 5.710153 > In my understanding, defining the genotype frequency as

This is as doumented, and I think you could say the same thing of seq(). BTW, sequence() allows negative inputs, and I don't think you want sum(input) in that case. I've never seen the point of sequence(), but it has been around in R for a long time. It is used in packages eRm, extRemes, hydrosanity, klaR, seas. Who knows what people have in private code, so I don't see any

Hello: If anyone could guide me with this I would greatly appreciate it. Thanking you in advance for your assistance. Using a 3-level input factor alternative so that a function(below) can compute both a two-sided and one-sided p-values. Making the two-sided test the default. And produce output information about which alternative was tested. Where would I place the ifelse statement?

> -----Original Message----- > From: linux-pci-owner at vger.kernel.org [mailto:linux-pci-owner at vger.kernel.org] > On Behalf Of Yijing Wang > Sent: Saturday, July 26, 2014 8:39 AM > To: linux-kernel at vger.kernel.org > Cc: Xinwei Hu; Wuyun; Bjorn Helgaas; linux-pci at vger.kernel.org; > Paul.Mundt at huawei.com; James E.J. Bottomley; Marc Zyngier; linux-arm- > kernel at

> -----Original Message----- > From: linux-pci-owner at vger.kernel.org [mailto:linux-pci-owner at vger.kernel.org] > On Behalf Of Yijing Wang > Sent: Saturday, July 26, 2014 8:39 AM > To: linux-kernel at vger.kernel.org > Cc: Xinwei Hu; Wuyun; Bjorn Helgaas; linux-pci at vger.kernel.org; > Paul.Mundt at huawei.com; James E.J. Bottomley; Marc Zyngier; linux-arm- > kernel at

This was sent to me by someone on the R-list ( I don't know her ) but I don't have time to look at this right now so I told her I would send it to the R-list because she said it keeps getting bounced when she sends it. #======================================================================= ==================================================================== I am a bit confused with

> -----Original Message----- > From: linux-pci-owner at vger.kernel.org [mailto:linux-pci-owner at vger.kernel.org] > On Behalf Of Yijing Wang > Sent: Saturday, July 26, 2014 8:39 AM > To: linux-kernel at vger.kernel.org > Cc: Xinwei Hu; Wuyun; Bjorn Helgaas; linux-pci at vger.kernel.org; > Paul.Mundt at huawei.com; James E.J. Bottomley; Marc Zyngier; linux-arm- > kernel at

> -----Original Message----- > From: linux-pci-owner at vger.kernel.org [mailto:linux-pci-owner at vger.kernel.org] > On Behalf Of Yijing Wang > Sent: Saturday, July 26, 2014 8:39 AM > To: linux-kernel at vger.kernel.org > Cc: Xinwei Hu; Wuyun; Bjorn Helgaas; linux-pci at vger.kernel.org; > Paul.Mundt at huawei.com; James E.J. Bottomley; Marc Zyngier; linux-arm- > kernel at

Dear list, This is a copy of a mail sent to Max Kuhn, original author and maintainer of the odfWeave package, which seems not to have received it. It reports a problem that seems to be very implementation specific (reproductible on three Debian testing amd64 machine, does *not* happen on two i686 Debian testing systems, does *not* happen on an Ubuntu 11.06 amd64 machine) and therefore not

Hello, Since people have whisperred about Rcpp, I'd like to play too. > On 11/15/2010 07:45 AM, Patrick Leyshock wrote: >> Very helpful, thank you. >> >> A couple other questions, please: >> >> 1. I've got a function written in C, named "my_c_function". In my R >> code I call this function, passing to it an INTSXP and a STRSXP, >>

pci_enable_msix currently returns -EINVAL if you ask for more vectors than supported by the device, which would typically cause fallback to regular interrupts. It's better to return the table size, making the driver retry MSI-X with less vectors. Signed-off-by: Michael S. Tsirkin <mst at redhat.com> --- Hi Jesse, This came up when I was adding MSI-X support to virtio pci driver, which

pci_enable_msix currently returns -EINVAL if you ask for more vectors than supported by the device, which would typically cause fallback to regular interrupts. It's better to return the table size, making the driver retry MSI-X with less vectors. Signed-off-by: Michael S. Tsirkin <mst at redhat.com> --- Hi Jesse, This came up when I was adding MSI-X support to virtio pci driver, which

Hi All, I would like to compute the simple finite-difference approximation to the gradient of a scalar function of a large number of variables (on the order of 1000). Although a one-time computation using the following function grad() is fast and simple enough, the overhead for repeated evaluation of gradient in iterative schemes is quite significant. I was wondering whether there are

Hi, I often have to do this: select a folder (directory) containing a few hundred data files in csv format (up to 1000 files, in fact) open each file, transform some character variables in date-tiime format make into a dataframe (involves getting rid of a few variables I don't need concatenate to the master dataframe that will eventually contain the data from all the files in the

Hello all, I would like some R function that can translate a string to a "URL encoding" (see here: http://www.w3schools.com/tags/ref_urlencode.asp) Is it implemented? (I wasn't able to find any reference to it) Thanks, Tal ----------------Contact Details:------------------------------------------------------- Contact me: Tal.Galili@gmail.com | 972-52-7275845 Read me:

Hi, I have the following dataset (simplified for example). __DATA__ 300.35 200.25 104.30 22.00 31.12 89.99 444.50 22.10 43.00 22.10 200.55 66.77 Now from that I wish to do the following: 1. Compute variance of each row 2. Pick top-2 row with highest variance 3. Store those selected rows for further processing To achieve this, I tried to: a) read the table and compute variance for each row,