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I have a file: x y z 0.025 0.025 1.65775 0.025 0.050 1.62602 0.025 0.075 1.63683 0.025 0.100 1.91847 0.025 0.125 2.00913 0.025 0.150 1.82222 0.025 0.175 1.70901 0.025 0.200 1.39759 0.025 0.225 1.39089 0.025 0.250 1.04762 If I read the file like this: data<-read.table("file.dat") How do I access the vectors x,y,z that are inside the dataframe data? I studied Venables and

If I have a table (we'll call it, "test") containing two columns (as below): i x1 x2 x3 x4 x5 y 0 1.125 0.232 7.160 0.0859 8.905 1.5563 7 0.920 0.268 8.804 0.0865 7.388 0.8976 15 0.835 0.271 8.108 0.0852 5.348 0.7482 22 1.000 0.237 6.370 0.0838 8.056 0.7160 29 1.150 0.192 6.441 0.0821 6.960 0.3130 37 0.990 0.202 5.154 0.0792 5.690 0.3617 44 0.840 0.184 5.896 0.0812 6.932 0.1139 58

Hi All, simple question: do you know how to graph the following object/matrix in a 'surface manner': [,1] [,2] [,3] [,4] [,5] [,6] [1,] -0.154 -0.065 0.129 0.637 0.780 0.221 [2,] 0.236 0.580 0.448 0.729 0.859 0.475 [3,] 0.401 0.506 0.310 0.650 0.822 0.448 [4,] 0.548 0.625 0.883 0.825 0.945 0.637 [5,] 0.544 0.746 0.823 0.877 0.861 0.642 [6,] 0.262 0.399

Dear R users, I'm trying to do betareg on my dataset. Dependent variable is not normally distributed and is proportion (of condom use (0,1)). But I'm having problems: gyl<-betareg(cond ~ alcoh + drug, data=results) Error in optim(par = start, fn = loglikfun, gr = gradfun, method = method, : initial value in 'vmmin' is not finite Why is R returning me error in optim()? What

Dear Thomas, The head of my dataset > head(wsuv) parcel sp time censo treatment species 1 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1 1 2 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1 1 3 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1 1 4 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1

Hi, I am using ccf but I could not figure out how to calculate the actual lag in number of periods from the returned results. The documentation for ccf says:"The lag is returned and plotted in units of time". What does "units of time" mean? For example: > x=ldeaths > x1=lag(ldeaths,1) > results=ccf(x,x1) > results Autocorrelations of series 'X', by lag

Working with 5 subset streams from my source data frame, three of them successfully call dcast(), but two fail: jerritt.cast <- dcast(jerritt.melt, site + sampdate ~ param) Aggregation function missing: defaulting to length and winters.cast <- dcast(winters.melt, site + sampdate ~ param) Aggregation function missing: defaulting to length Yet both data frames have the values in their

Hello all, I am working with a 1000x1000 matrix, and I would like to return a 1000x1000 matrix that tells me which value in the matrix is greater than a theshold value (1 or 0 indicator). i have tried mat2<-as.matrix(as.numeric(mat1>0.25)) but that returns a 1:100000 matrix. I have also tried for loops, but they are grossly inefficient. THanks for all your help in advance. Lanre

Hi All, I was wondering if someone could help me to solve this issue with lmer. In order to understand the best mixed effects model to fit my data, I compared the following options according to the procedures specified in many papers (i.e. Baayen <http://www.google.it/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CDsQFjAA

Hello all, here's a real-world example: I'm measuring a quantity (d) at five sites (site1 thru site5) on a silicon wafer. There is a clear site-dependence of the measured value. To find out if this is a measurement artifact I measured the wafer four times: twice in the normal position (posN), and twice rotated by 180 degrees (posR). My data looks like this (full, self-contained code at

Hi, I have a big data frame: > mat <- matrix(rep(paste(letters, collapse=""), 5*300000), ncol=5) > dat <- as.data.frame(mat) and I need to do some computation on each row. Currently I'm doing this: > for (key in row.names(dat)) { row <- dat[key, ]; ... do some computation on row... } which could probably considered a very natural (and R'ish) way of

Dear R users, I need to fit an ARMA model. As far as I've seen, EACF (extended ACF) is not available in R. 1. Let's say I fit a series of ARMA models in a loop. Given the code/output included below, how do I pull 'Model' and 'Fit' (AIC) from each summary() so that I can combine them into an array/data frame to be sorted by AIC? 2. Apart from EACF, are you aware perhaps

Hello I would like to transfer some Splus functions in R. But I have a problem first about this assignation in Splus : xnom <- deparse(substitute(x)) I am a bad programmer : I don't understand the R help How to modify these functions ? Thank you very much for your help Here are the four functions and a data test

All - Each time through a loop I create a new dataset, which I would like to append to a list object. Each item of the list should be the data matrix created in that step of the loop; I would like the NAME (or tag) of that list item to be assigned the value of a character string: I've tried something like this: running.list <- numeric(0) for(i in 1:num.files){ ..... running.list

I am trying to use the SeasonalMannKendall function in the Kendall package. My dataset (alb_data) is in the same format as the example dataset (manaus) in the package. > class(manaus) [1] "ts" > is.ts(manaus) [1] TRUE > typeof(manaus) [1] "double" > alb_data=read.table("R:/albemarle_manken.txt", header=T) > head(alb_data) year Jan Feb

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

Dear Thierry, thank you for the quick reply. I have only one question about the approach you proposed. As you suggested, imagine that the model we end up after the model selection procedure is: mod2.1 <- lmer(dT_purs ~ T + Z + (1 +T+Z| subject), data =x, REML= FALSE) According to the common procedures specified in many manuals and recent papers, if I want to compute the p_values relative to

Thank you very much for your reply. Your code work well with this example. I modified a little to fit my real data, I got an error massage. Error in split.default(x = seq_len(nrow(x)), f = f, drop = drop, ...) : Group length is 0 but data length > 0 On Thu, Jan 31, 2013 at 12:21 PM, arun kirshna [via R] < ml-node+s789695n4657196h87@n4.nabble.com> wrote: > Hi, > Try this: >

i have a data frame(dat) which has many variables.and i use the following script to get the crosstable. >danx2<-c("x1.1","x1.2","x1.3","x1.4","x1.5","x2","x4","x5","x6","x7","x8.1","x8.2","x8.3","x8.4","x11",

This is a general question about Design of experiments. If i am not allowed to post general questions like this here please accept my apologies and ignore the question. I did a DOE with six factors in eight runs. I know i cannot check for interactions using this design, but i tried the interaction plot and it showed me many interactions. After this I foldover the design and ran the 8 runs to learn