similar to: multiple frequencies per second again

Hi all, I wanted to mark the estimation sample: mark what rows (observations) are deleted by lm due to missingness. For eg, from the original example in help, I have changed one of the values in trt to be NA (missing). # code below # ---- # original example > ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14) > trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69) #

Dear Dr.Goslee and anyone may intrested in matrix manipulate, I am using your ecodist to do mantel and partial mantel test, I have locality data and shape variation data, and the two distance matrixs are given as belowings. When I run the analysis, it is always report that the matrix is not square, but I didn't know what's wrong with my data. Would you please help me on this. I am quite

Dear R-helpers, I have two data frames, op and em4: > str(op) 'data.frame': 37 obs. of 5 variables: $ m : num 0.202 0.336 0.122 0.139 0.14 ... $ lln : num 0.798 0.643 0.863 0.835 0.823 ... $ rrn : num 0.789 0.702 0.894 0.895 0.923 ... $ asym2: num 0.177 0.304 0.108 0.187 0.274 ... $ asym3: num 0.0755 0.0975 0.0818 0.0651 0.13 ... > str(rownames(op)) chr

Hi all, I'm seeing this failure on my PPC G4 box running TOT with llvm-gcc 4.2. Is anyone else seeing this? I'm sure it's related to the byval stuff that's recently gone into LLVM. I'm attaching the output of this command: $ llvm-gcc -emit-llvm -O3 -S -o - -emit-llvm /Users/wendling/llvm/ llvm.src/test/CFrontend/2008-01-25-ByValReadNone.c As you can see in it, there

Hi, I have a data set with 999 observations, for each of them I have data on four variables: site, colony, gender (quite a few NA values), and cohort. This is how the data set looks like: > str(dispersal) 'data.frame': 999 obs. of 4 variables: $ site : Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 2 2 ... $ gender: Factor w/ 2 levels "0","1":

On Mon, Dec 16, 2013 at 04:16:29PM -0800, Michael Dalton wrote: > Commit 2613af0ed18a ("virtio_net: migrate mergeable rx buffers to page frag > allocators") changed the mergeable receive buffer size from PAGE_SIZE to > MTU-size, introducing a single-stream regression for benchmarks with large > average packet size. There is no single optimal buffer size for all >

On Mon, Dec 16, 2013 at 04:16:29PM -0800, Michael Dalton wrote: > Commit 2613af0ed18a ("virtio_net: migrate mergeable rx buffers to page frag > allocators") changed the mergeable receive buffer size from PAGE_SIZE to > MTU-size, introducing a single-stream regression for benchmarks with large > average packet size. There is no single optimal buffer size for all >

Hallo, I have this dataset with repeated measures. There are two within-subject factors, "formant" (2 levels: 1 and 2) and "f2 Ref" (25 levels: 670, 729, 788, 846, 905, 1080, 1100, 1120, 1140, 1170, 1480, 1470, 1450, 1440, 1430, 1890, 1840, 1790, 1740, 1690, 2290, 2210, 2120, 2040, 1950), and one between-subject factor, lang (2 levels:1 and 2). The response variable

Hi LLVM-ites! We are doing a quick test of 3.3rc3. Our testers did a quick turn around and created binaries which you can test. Please give them a go and let us know how they work for you. They are here: http://llvm.org/pre-releases/3.3/rc3 We don't have a lot of time remaining in the release cycle, so please do whatever you can to make sure they are solid. In particular, make sure that

It's probably PR12517. Looking at the clang binary, it's got a /home/ dir in RPATH: $ objdump -p clang+llvm-3.3rc3-Ubuntu-12.04.2-x86_64/bin/clang | grep RPATH RPATH $ORIGIN/../lib:/home/aadgrand/tmp/LLVM-3.3rc3/rc3/Phase3/Release+Asserts/llvmCore-3.3-rc3.obj/Release+Asserts/bin This will slow things down if the system tries to automount /home/aadgrand. Maybe we should merge r182559

Hello, I'm running a number of arima models using the "arima" function. Often, when lag length gets too high, these model don't converge and an error message appears as this: > reg <- arima(y,order=c(7,0,7),xreg=isr) Warning message: In arima(y, order = c(7, 0, 7), xreg = isr) : possible convergence problem: optim gave code=1 In this case, when you print the results

*H*i, I am trying to fit a GEE model with *geeglm* function. The model is the following: Modelo<-geeglm(sqrt ~Tra+ Mes, id=Lugar , data=datos, family=gaussian(identity), corstr="independence") *Tra( is a experimental treatment, 2 levels)*, *Mes* (is the month of take data, 4 levels) and *Lugar* (is the site of study, 3 levels) are categorical variables and *sqrt* (sqrt of Total

Hi to all I hope you can help me. # I'm trying to plot the following ratio data with standard error bars (horizontal). ratioBiomass <- c(1.327, 0.865, 1.900, 0.992, 1.469, 1.381, 1.230,1.269, 2.411, 1.288, 1.861, 0.714, 1.341, 1.362, 1.065, 2.374) SEratio <- c(19.28, 5.04, 0.01, 0.01, 0.90, 0.02, 0.002, 11.37, 0.004, 0.29, 0.003, 0.13, 0.21, 0.52, 1.66, 14.57) Species <-

Dear list, I have the following matrix. How can I make the following plot? 1. The x-axis has index 1:7, and the first column is plotted against index 1, second against 2, and so on. 2. I want the points from the left upper conner including the antidiagonal to be plotted with col=2, and the rest with col=3 [,1] [,2] [,3] [,4] [,5] [,6] [,7] [1,] 0.589 0.857 0.923 0.944 0.954 0.963

Hello R helpers: *My first message didn't pass trough filter so here it's again* I would like to obtain probability of an event for one single patient as a function of time (from survfit.coxph) object, as I want to find what is the probability of an event say at 1 month and what is the probability of an event at 80 months and compare. So I tried the following but it fails miserably. I

Hi R-people, I performed controlled experiments to evaluated the seeds germination of two palms under four levels of water treatments. I conducted a generalized linear model (GLM) with a Poisson distribution to verify whether there were significant differences in the number of seed germination (NS-count variable) between treatments and species (explanatory variables). Thus, my model and output

Hi, I got two data point vectors. Now I want to make a ks.test(). I you print both vectors you will see, that they fit pretty fine. Here is a picture: http://www.jochen-bauer.net/downloads/kstest-r-help-list-plot.png As you can see there is one histogram and moreover there is the gumbel density function plotted. Now I took to bin-mids and the bin-height for vector1 and computed the

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

Hi: I am using a subset of the below dataset to predict PRED_SUIT for the whole dataset but I am having trouble with 'newdata'. The model was created with 153 records and want to predict for 208 records. wolf2 <- structure(list(gridcell = c(367L, 444L, 533L, 587L, 598L, 609L, 620L, 629L, 641L, 651L, 662L, 674L, 684L, 695L, 738L, 748L, 804L, 805L, 872L, 919L, 929L, 938L, 950L, 958L,

Hi Bill, I was running some benchmarks and was surprised that the startup performance of your binaries is much worse than the stable binaries for 3.2 I've used: http://llvm.org/releases/3.2/clang+llvm-3.2-x86_64-linux-ubuntu-12.04.tar.gz vs http://llvm.org/pre-releases/3.3/rc3/clang+llvm-3.3rc3-Ubuntu-12.04.2-x86_64.tar.gz On a simple hello.c file: /ssd/bench$ TIMEFORMAT="%E"