similar to: Separating variables in read.table

Hello I wonder how to change the font of chart to Times New Roman and size 9. plot(c(0,100,20),c(0,600,50), xlab= 'Idade(meses)', ylab="Peso(kg)", type = "n", axes=F) axis(1, pos=0, at=seq(0,100,20)) axis(2, pos=0, at=seq(0,600,100)) t<- seq(0,100,1) TA=543.56*(1-0.8976*exp(-0.0522*t)) NI=498.97*(1-0.9259*exp(-0.0494*t)) RC=514.57*(1-0.9112*exp(-0.0499*t))

*Dear R users, Ive just started using the ff package. There is a csv file (~4Gb) with 7 columns and 6e+7 rows. I want to read only column from the file, skipping the first 100 rows. Below Ive provided different outcomes, which will clarify my problem * > sessionInfo() R version 2.14.2 (2012-02-29) Platform: x86_64-pc-mingw32/x64 (64-bit) locale: ... attached base packages: [1] tools

Hi there, The following data is obtained from a long-term experiments. > mydata <- read.table(textConnection(" + y year Trt + 9.37 1993 A + 8.21 1995 A + 8.11 1999 A + 7.22 2007 A + 7.81 2010 A + 10.85 1993 B + 12.83 1995 B + 13.21 1999 B + 13.70 2007 B + 15.15 2010 B + 5.69 1993 C + 5.76 1995 C + 6.39 1999

I have a table like the following. I want to fit Cm to Vm like this: Cm ~ Cl+Q1*b1*38.67*exp(-b1*(Vm-Vp1)*0.03867)/(1+exp(-b1*(Vm-Vp1)*0.03867))^2+Q2*b2*38.67*exp(-b2*(Vm-Vp2)*0.03867)/(1+exp(-b2*(Vm-Vp2)*0.03867))^2 I use nls, with start=list(Q1=2e-3, b1=1, Vp1=-25, Q2=3e-3, b2=1, Vp2=200). But I always get 'singlular gradient' error like this. But in SigmaPlot I can get the result. How

Dear all, I am trying to use the crr function in the cmprsk package version 2.2 to analyse 198 observations.I have receive the error in solve.default. Can anyone give me some insights into where the problem is? Thanks here is my script : cov=cbind(x1,x2) z<-crr(ftime,fstatus,cov)) and data file: x1 x2 fstatus ftime 0 .02 1 263 0 .03 1 113 0 .03 1 523

Dear R gurus, I am looking for a way to fit a predictive model for a contingency table which has counts. I found that glm( family=poisson) is very good for figuring out which of several alternative models I should select. But once I select a model it is hard to present and interpret it, especially when it has interactions, because everything is done "relative to reference cell". This

HI I use glm in R to do logistic regression. and treat both response and predictor as factor In my first try: ******************************************************************************* Call: glm(formula = as.factor(diagnostic) ~ as.factor(7161521) + as.factor(2281517), family = binomial()) Deviance Residuals: Min 1Q Median 3Q Max -1.5370 -1.0431 -0.9416 1.3065 1.4331 Coefficients:

Hello R users I'm using MuMIn but for some reason I'm not getting the adjusted confidence interval and uncoditional SE whe I use model.avg(). I took into consideration the steps provided by Grueber et al (2011) Multimodel inference in ecology and evolution: challenges and solutions in JEB. I created a global model to see if malaria prevalence (binomial distribution) is related to any

Hi list, I'm attempting to re-create a Repeated Measures Compositional Analysis as described in the work by Aebischer et. al. (Ecology. 1993. 74(5): 1313-1325). In this paper they describe transitions of data into a log ratio difference matrix, from which they obtain two matrices using a monova routine. I am able to produce the second of the two matrices, but I'm having trouble

[I am herewith re-posting this message on R-devel, as it seems to be the most appropriate mailing list for this issue.] Dear List, >From what I understand, strptime() simply converts from one class representation to another; i.e., from character to POSIXct/POSIXlt. One strange feature of this command running on Linux is that there are repeated calls to system time (as was revealed

Update, after few hours of qemu uptime I can see this oreport: 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 % linenr info image name symbol name ------------------------------------------------------------------------------- 385793

Dear All: Could you please tell me how I can draw figure formatted like figure 4.18 of MASS (4th) with the attached data set? Thanks Zhongming Yang --------------------------------- -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... Name: sample.txt Url: https://stat.ethz.ch/pipermail/r-help/attachments/20050316/abfdb85e/sample.txt

When the binary search returns 0 (exact match), the target key will necessarily be at slot 0 of all nodes below the current one, so in this case the binary search is not needed because it will always return 0, and we waste time doing it, holding node locks for longer than necessary, etc. Below follow histograms with the times spent on the current approach of doing a binary search when the

This nightly tester is now using an llvm-g++ that produces the new ODR linkage types. This means that many more functions are being considered by the inter-procedural optimization passes (for example, "linkonce" functions defined in a header). The result seems to be pretty huge swings (both good and bad) in the C++ tests in the testsuite, see below. Note that this tester is often

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 am trying to find m breakpoints of a linear regression model. I used the segmented package. It works fine for small number of predicators and breakpoints.(3 r.v. 3 points). However, my model has 14 variables it even would not work even for just one breakpoints!. The error message is always estimated breakpoints are out of range. Since my problem is time related problem. So I

(The list appears to have eaten my previous attempt to send this. Apologies if you receive multiple copies.) The attached patches allow you to use paravirtualised network and block interfaces from fully virtualised domains, based on Intel''s patches from a few months ago. These are significantly faster than the equivalent ioemu devices, sometimes by more than an order of magnitude.