similar to: Error in apply(x2, 1, diff) : dim(X) must have a positive length

Hi!! I am trying to multiply 5 matrices and then using the inverse of that matrix for further computation. I read about precision problems from the archives and the suggestion was to use as.numeric while computing the products. I am still having problems with the results. Here is how I am using it #Mn.mat<-(T.mat %*% Rz.mat %*% Q.mat %*% Rz.mat %*% T.mat) # I was doing this in one step

Hi list, In the object returned by summary.nlsList, what's the difference between "coefficients" and "parameters"? The have the same "Estimate", different se (therefore t value), but same p values. R.2.8.0 on winxp with nlme_3.1-89 Thanks, ...Tao +++++++++++++++++++++++++++++++++++++++++++++++++ > library(nlme) > fm1 <- nlsList(uptake ~

Hi, I'm very new to R and absolutely love it. Does anyone know how to use something in R that functions like a BY command in SAS? For example, let's say you have a variable x, and you want to see the mean. Easy... > mean(x) But what if you want to see the mean of x conditional on another discrete variable? My best attempts so far are something like... > mean(x, y_cat=1)

Hi, I just started a new course this semester on R, I never used it in my life and i'm stuck on these questions from 3 days, it would be really nice if someone could explain me the answers with the relative commands. thanks a lot in advance The following 7 questions are based on the CO2 dataset of R. 1) How many of the plants in CO2 are Mc2 for Plant? 2) How many are either Mc2 or Mn2?

# Your mailer is set to "none" (default on Windows), # hence we cannot send the bug report directly from R. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs@r-project.org # ###################################################### # The last line of following code produces a segmentation fault: x <- 1:10 f <- gl(5,2)

Hi, For further calculations I need to extract indivdual Variances of different random effects from a fitted model. I found out how to extract the correlations (VarCorr(m1)@reSumry$group1) but I was not able to find a way to extract the other components individually. To extract the Residuals I tried: (ranef(m1)@ stdErr) which unfortunately did not work. Thank you very much for your help!

Hi, Using library(lattice), is there any way to tell xyplot to plot panels top to bottom, then left to right (i.e. panels are appended vertically, then horizontally). as.table changes the plot direction from left-to-right then top-to-bottom, to right-to-left then bottom- to-top, but that's not quite what I want to do. Thanks Yan

Hi all, Very surprising (to me!) and mystifying result from predict.glm(): the predictions vary depending on whether or not I use ns() or splines::ns(). Reprex follows: library(splines) set.seed(12345) dat <- data.frame(claim = rbinom(1000, 1, 0.5)) mns <- c(3.4, 3.6) sds <- c(0.24, 0.35) dat$wind <- exp(rnorm(nrow(dat), mean = mns[dat$claim + 1], sd = sds[dat$claim + 1])) dat <-

Hi, I have a data frame like this: ScoreDoseSex 2.81Dose1M 1.81Dose1M 1.22Dose1M 0.81Dose1M 0.49Dose1M 0.22Dose1M 0.00Dose1M -0.19Dose1M -0.17Dose1F -0.32Dose1F -0.46Dose1F -0.58Dose1F -0.70Dose1F -0.81Dose1F -0.91Dose1F -1.00Dose1F -1.77Dose2M -1.85Dose2M -1.93Dose2M -2.00Dose2M -2.07Dose2M -2.14Dose2M -2.20Dose2M -2.26Dose2M -2.32Dose2F -2.38Dose2F -2.17Dose2F -2.49Dose2F -2.54Dose2F

Hi all, I am looking for a function for following calculation. start.month = "July" end.month = "January" months = f(start.month, end.month, by=1) * f is the function that I am looking for. Actually I want to get months = c("July", "August",.............."January") If start.month = 6 and end.month = 1 then I could use (not properly) seq()

Dear Help I'm new to R (from matlab)...using windows XP. I've tried to work out, to no avail, 4 things: 1) rotating the numbers on axes...something to do with par(str) ?? 2) how to close a window having opened one e.g. windows(7,7) 3) how to manipulate the key (e.g. dots, lines etc) on the legend. Using pch just gives me the same key for all functions on a plot. i.e. legend

Hello everybody, On the documentation page for the tailcallelim pass you can read: "This pass transforms functions that are prevented from being tail recursive by an associative expression to use an accumulator variable, thus compiling the typical naive factorial or fib implementation into efficient code” However, I don’t see this behavior when trying to compile this variant of the

Dear all, Sorry to bother you with one more newbie question. I have a dataobject with several hundreds of columns. I want to remove columns with a mean of the column values below a certain value: > a<- c(1,2,3,4,5,6) > b<-c(2,4,6,8,10,12) > c<- c(3,6,9,12,15,18) > test<- as.matrix(cbind(a, b, c)) > mean(a) [1] 3.5 > mean(b) [1] 7 > mean(c) [1] 10.5 Say the

I have a list of 20 values. The first time through a loop I want to find the mean and stnd.dev. of the first two values; the second time through the loop I want to find the mean and stnd. dev. of the first 3 values, etc. until the last time through the loop I want to find the mean and stnd. dev. of all 20 values, so I end up with 19 means and stnd. deviations. How would I construct such a loop?

Dear R-Help, My problem/bug came to light,when fitting a linear model using stepwise selection. I'd started with the straightfoward command step(lm(y~., dataset)) This worked fine, but because this starts with all the possible explanatory variables, it results in a model with too many explanatory variables. Hence I wanted to start with just a constant and do forward selection, to get a

Dear R users, I am using the Match function to generate nearest neighbor matching estimators. On that front I am ok, but where I am having problems is getting my output into nice LaTeX tables. Here is some basic code imitating the estimation I'm doing. No problem there. library(Matching) #make up some data X1 <- matrix(rnorm(1000*5), ncol=5) Y1 <- as.vector(rnorm(1000)) Tr1 <-

Hi, what I would need are 2 vector pairs (x,y) and (x1,y1). x and x1 must have the same sd. y and y1 should also exhibit the same sd's but different ones as x and x1. Plotting x,y and x1,y1 should produce a plot with 2 vectors having a different slope. Plotting both vector pairs in one plot with fixed axes should reveal the different slope. many thanks syrvn -- View this message in

I'm trying to figure out about factors, however the on-line documentation is rather sparse. I guess, factors are intended for grouping arrays members into categories, which R names "Levels". And so we have: * state <- c("tas", "sa", "qld", "nsw", "nsw", "nt", "wa", "wa",

Hi Guys, stumped by a simple problem. I would like to take a file of the form Pair group param1 1 D 10 1 D 10 1 R 10 1 D 10 2 D 10 2 D 10 2 D 10 2 R 10 2 R 10 etc.. and for each pair, calculate the average of

I am using R for the first time in one of my classes. My students have alerted me to a problem for which we have not found an answer. We find that some means returned by the model.tables function are not correct when missing data is present in analysis of variance problems. We have duplicated the problem using R 1.2.0, 1.2.1, and 1.2.2 under Windows 98 and several distributions of Linux (Redhat