search for: 0.0042

Dear sir, I am extremely sorry for messing up the logic asking for help w.r.t. my earlier mails   I have tried to explain below what I am looking for.     I have a database (say, currency_rates) storing datewise currency exchange rates with some base currency XYZ.   currency_rates <- data.frame(date = c("12/31/2010", "12/30/2010", "12/29/2010",

    I created a couple of timeSeries objects - when I was merging them , I got an error. Looking at the data , I see that one of the time series has   06/30/2007  0.0028       0.0183  0.0122      0.0042  0.0095    -          07/31/2007 -0.0111       0.0255  0.0096     -0.0069 -0.0024  0.0043       08/31/2007 -0.0108      -0.0237 -0.0062     -0.0138 -0.0173 -0.0065       09/30/2007 

My mistake sir. I was literally engrossed in my stupid logic, and while doing so, overlooked the simple and very effective solution you had offered. Sorry once again sir and will certainly try to be very careful in future. Thanks again and have a great weekend sir. Regards Amelia --- On Fri, 7/1/11, Petr PIKAL <petr.pikal@precheza.cz> wrote: From: Petr PIKAL

Hello, I have got two matrices with different length. The matrices have 3 columuns. The first two are coordinates. The third is a measurement. Now I want to get a subtraction between every single value of the third column (between matrix1 and matrix2), but only if the two first coordinates in matrix1 and matrix2 are the same. I tried "FUN=?" in aggregate and ave, but I don't know

Dear all, Suppose I have a linear mixed-effects model (from the package nlme) with nested random effects (see below); how would I present the results from the random effects part in a publication? Specifically, I?d like to know: (1) What is the total variance of the random effects at each level? (2) How can I test the significance of the variance components? (3) Is there something like an

Hi everybody, this is a real dummy thing. I sorted a matrix based on a given column, and what I get is right, until it comes to columns of negative and positive values; than, "order" orders everything from max to min in the negative values, and then AGAIN from max to min in the positive values!!! Why isn't everything order from max to min, and that's it? Thank you!!! Attached

Dear all, I'm using R 2.8.1 under Windows Vista on a dual core 2,4 GhZ with 4 GB of RAM. I'm trying to reproduce a result out of "Analysis of Financial Time Series" by Ruey Tsay. In R I'm using the fGarch library. After fitting a ar(3)-garch(1,1)-model > model<-garchFit(~arma(3,0)+garch(1,1), analyse) I'm saving the results via > result<-model

I was testing Ilia's patches for ddx, and while they definitely helped for Xorg itself, qemu still eats a lot of CPU if launched like this qemu-system-x86_64 -cdrom ~/Downloads/ISO/slax-English-US-7.0.8-x86_64.iso -m 1G -display sdl,gl=on -enable-kvm and left for few hours. top - 07:38:01 up 18:05, 2 users, load average: 2,00, 1,89, 1,83 Tasks: 224 total, 3 running, 221 sleeping, 0

Dear Spencer and Prof. Fox, Thank you for your replies. I'll very appreciate, if you have any ideas concerning the problem described below. First, I'd like to describe the model in brief. In general I consider a model with three equations. First one is for annual GRP growth - in general it looks like: 1) GRP growth per capita = G(investment, migration, initial GRP per

Dear, We are trying to determine the (one-sided) CI for the coefficient of variation in a small sample (say n = 10), with mean 100 and standard deviation 21. It appears though that the R-function ci.cv() and our simulation do not agree. The R-code: library(MBESS) n = 10 ci.cv(mean = 100, sd = 21, n = 10, conf.level = 0.9) U10.95 <- 0.3551754 ci.cv(mean = 100, sd = 21, n = 10, conf.level =

The DDX eating CPU isn't intrinsically bad. Did you check where perf says the CPU time is going? Could be doing copies/etc. On Mon, Aug 17, 2020 at 12:52 AM Andrew Randrianasulu <randrianasulu at gmail.com> wrote: > > I was testing Ilia's patches for ddx, and while they definitely helped for Xorg itself, > qemu still eats a lot of CPU if launched like this > >

Dear all, Suppose I have a linear mixed-effects model (from the package nlme) with nested random effects (see below); how would I present the results from the random effects part in a publication? Specifically, I?d like to know: (1) What is the total variance of the random effects at each level? (2) How can I test the significance of the variance components? (3) Is there something like an

Target: FreeBSD 7.0-RC1 on amd64. autoconf says: configure:2122: checking build system type configure:2140: result: x86_64-unknown-freebsd7.0 [...] configure:2721: gcc -v >&5 Using built-in specs. Target: amd64-undermydesk-freebsd Configured with: FreeBSD/amd64 system compiler Thread model: posix gcc version 4.2.1 20070719 [FreeBSD] [...] objdir != srcdir, for both llvm and gcc. Release

A big compile time regression. Any ideas? Ciao, Duncan. On 22/07/11 19:13, llvm-testresults at cs.uiuc.edu wrote: > > bwilson__llvm-gcc_PROD__i386 nightly tester results > > URL http://llvm.org/perf/db_default/simple/nts/253/ > Nickname bwilson__llvm-gcc_PROD__i386:4 > Name curlew.apple.com > > Run ID Order Start Time End Time > Current 253 0 2011-07-22 16:22:04

At 2013-09-09 13:07:07,"Tobias Grosser" <tobias at grosser.es> wrote: >On 09/09/2013 05:18 AM, Star Tan wrote: >> >> At 2013-09-09 05:52:35,"Tobias Grosser" <tobias at grosser.es> wrote: >> >>> On 09/08/2013 08:03 PM, Star Tan wrote: >>> Also, I wonder if your runs include the dependence analysis. If this is >>> the

LLVMers, The 2.2 prerelease is now available for testing: http://llvm.org/prereleases/2.2/ If anyone can help test this release, I ask that you do the following: 1) Build llvm and llvm-gcc (or use a binary). You may build release (default) or debug. You may pick llvm-gcc-4.0, llvm-gcc-4.2, or both. 2) Run 'make check'. 3) In llvm-test, run 'make TEST=nightly report'. 4) When

All, How come both of these are the same. Both say "1-sample proportions test without continuity correction." I would suspect one would say "without" and one would say "with." > prop.test(118,236,.5,correct=FALSE,conf.level=0.95) 1-sample proportions test without continuity correction data: 118 out of 236, null probability 0.5 X-squared = 0, df = 1,

Hi all, I've started looking at the GlobalMerge pass, enabled by default on ARM and AArch64. I think we should reconsider that, at least for AArch64. As is, the pass just merges all globals together, in groups of 4KB (AArch64, 128B on ARM). At the time it was enabled, the general thinking was "it's almost free, it doesn't affect performance much, we might as well use it".

Dear all, It was a pleasure to meet you at Iowa State University. Two days ago I submitted two experimental packages to CRAN (hope it will be there soon): rindex: quick indexing of large objects (currently only character, see ?index) regtest: some first support for automated regression testing (heavily used in \dontshow{} section of ?index) With rindex you can for example i <-

I rebuild mesa with debug symbols, and now top functions using CPU looks like this: CPU: AMD64 family15h, speed 3800 MHz (estimated) Counted CPU_CLK_UNHALTED events (CPU Clocks not Halted) with a unit mask of 0x00 (No unit mask) count 100000 samples % image name symbol name ------------------------------------------------------------------------------- 222978 45.1489