similar to: Problem with command apply

Hi, I'm stuck on creating a plot with x tick labels for every Nth tick mark - how is that done? I don't see a simple solution to this in help(plot) or help(par) and what I've tried is not working, eg, the following does not work, although it seems intuitive to me that it should work: x <- seq(-100,1000,25) y <- x * x % find all the x values that are multiples of 100 tmp <-

Dear list I'm testing a predictor and I produced nice performance plots with ROCR package utilizing the 3 standard command pred <- prediction(predictions, labels) perf <- performance(pred, measure = "tpr", x.measure = "fpr") plot(perf, col=rainbow(10)) The pred object and the perfo object are S4 with the following slots An object of class "performance"

Hi all, This seems like a basic problem, but no amount of playing with the code has solved it. I have a time-series data set like that shown below (only longer) and am seeking to plot the data with filled, circular points and error bars. I would like the error bars to be behind the points otherwise they tend to obscure the points (especially when I have a lot of points in the actual data set).

Hello. Consider the following matrix: mp <- matrix(c(0,1/4,1/4,3/4,0,1/4,1/4,3/4,1/2),3,3,byrow=T) > mp [,1] [,2] [,3] [1,] 0.00 0.25 0.25 [2,] 0.75 0.00 0.25 [3,] 0.25 0.75 0.50 The eigenvectors of the previous matrix are 1, 0.25 and 0.25 and it is not a diagonalizable matrix. When you try to find the eigenvalues and eigenvectors with R, R responses: > eigen(mp) $values [1]

I start a clean session of R 1.9.1 on Windows and I run the following code: > library(MASS) > data(painters) > pca.painters <- princomp(painters[ ,1:4]) > loadings(pca.painters) Loadings: Comp.1 Comp.2 Comp.3 Comp.4 Composition 0.484 -0.376 0.784 -0.101 Drawing 0.424 0.187 -0.280 -0.841 Colour -0.381 -0.845 -0.211 -0.310 Expression 0.664 -0.330 -0.513

Hi, i am new to this forum and not sure how it works, I am trying to do deskriptive descripe my data in terms of gender: head(scltotal) pbnr dat dep dys sop ago mis age female messpunkt2 messpunkt1 tage eintrittsjahr 1 10023 1994-02-21 0.75 1.00 0.50 0.50 0.75 35 1 8817 8817 0 1994 2 10023 1994-05-25 0.75 1.00 0.50 0.50 0.75 35 1 8910 8817

Hi, I'm trying to create a distance matrix. And it works out somewhat ok. However, I suspect that there are some efficiency issues with my efforts. Plz have a look at this: donor <- matrix(c(3,1,2,3,3,1,4,3,5,1,3,2), ncol=4) receiver <- matrix(c(1,4,3,2,4,3,1,5,1,3,2,1,4,5,3,5,1,3,2,4,5,1,2,3,1,4,5,5,1,2,1,3,4,3,2,5,5,1,4,2,5,4,3,2), ncol=4) The above creates my two matrices. I have

I have written a wrapper for heatmap.2 called heatmap.w.row.and.col.clust which auto-generates breaks using breaks<-round((c(seq(from=(-20 * stddev), to=(20 * stddev))))/20, digits = 2) #(stddev in this case = 2.5) This has always worked well in the past but now I am getting an error that non-finite breaks are being generated. Drilling down, it seems that my wrapper is generating finite

Hello there, I don't know if I'm addressing my question to the right e-mail address, I hope I do. Actually I have a little problem concerning writing a code in R. I try to briefly sum up my problem. As you can see below, I created the functions "Equation1" and "Equation2" with some conditions. Equation1 <-function(x){ if

Greetings: It would seem to me that the three arguments "a", "c" and "p" ought to produce the same result with a data frame that doesn't have any missing data which is not the case. What am I doing wrong or what don't I understand? > tmp <- data.frame(vol,con,mot,esp,pri,sec) > tmp vol con mot esp pri sec 1 1.00 120 90 78 21 1 2 0.50

Hello, I am trying to create multiple matrices (to run a PVA) but can't import all of them from a .csv without the numbers treated as labels and not factors. I can enter the matrix slowly: Site05_96 <- matrix(c(0.07,0,0.03,0.00,NA,0.00, 0.09,0.166666667,0.31,0.42,NA,0.00, 0.00,0,0.00,0.00,NA,0.00, 0.00,0,0.00,0.00,NA,0.00,

Dear all, I have some trouble understanding the chisq.test function. Take the following example: set.seed(1) A <- cut(runif(100),c(0.0, 0.35, 0.50, 0.65, 1.00), labels=FALSE) B <- cut(runif(100),c(0.0, 0.25, 0.40, 0.75, 1.00), labels=FALSE) C <- cut(runif(100),c(0.0, 0.25, 0.50, 0.80, 1.00), labels=FALSE) x <- table(A,B) y <- table(A,C) When I calculate the test statistic by hand

Dear R Should I be concerned if the loadings to a Principle Component Analysis are as follows: Loadings: Comp.1 Comp.2 Comp.3 Comp.4 X100m -0.500 0.558 0.661 X200m -0.508 0.379 0.362 -0.683 X400m -0.505 -0.274 -0.794 -0.197 X800m -0.486 -0.686 0.486 0.239 Comp.1 Comp.2 Comp.3 Comp.4 SS loadings 1.00 1.00 1.00 1.00 Proportion Var 0.25 0.25 0.25

Dear R folk: Perhaps I'm just dense today, but I am having trouble reproducing the principal components plotted and summarized by clusplot. Here is a brief example using the pluton dataset. clusplot reports that the first two principal components explain 99.7% of the variability. But this is not what princomp is reporting. I would greatly appreciate any advice. With best regards, -- Tom

Hi all, I've got a matrix of fractional data that is all positive and greater than zero that I would like to "loosely" classify, for lack of a better word. It looks something like this : 1.07 1.11 1.27 1.59 0.97 0.76 2.23 0.98 0.71 0.88 1.19 1.02 What I'm looking for is a way to round these numbers to the nearest 0.25, i.e. the above matrix would be

I have panel data in the following form: TIME X1 S1 1 1 0.99 1 2 0.50 1 3 0.01 2 3 0.99 2 1 0.99 2 2 0.25 3 3 0.75 3 2 0.50 3 1 0.25 ... ... ...... And desire a new vector of observations in which one column (S1 above) is sorted for each second from least to largest. That

Dear list, I have observed a weird behaviour from R --- apologies if I am missing something obvious! df3f826f28 df3f826f28 Say you type in R: >c.preec <- 10074 >c.gd <- 2200 >p1 <- .2 >c.neo <- p1*9451 + (1-p1)*3883 >n.preec <- 3710 >n.gd <- 2650 >n.neo <- 2120 >n.pcos <- 53000 >unit.met <- 94 >cost.met <- 94*n.pcos >effect <-

R 2.10 Windows 7 I am trying to plot three graphs on top of each other. I need to have the axises perfectly aligned. For some reason the ticks on the y axes are slightly off so they do not perfectly align. Can someone tell me how I can get the to overlay each other perfectly? I thought the yaxp parameter would solve my problem, but it does not. My data and code follows: >

On 2016-05-25 19:13, Kelly Lesperance wrote: > Hdparm didn?t get far: > > [root at r1k1 ~] # hdparm -tT /dev/sda > > /dev/sda: > Timing cached reads: Alarm clock > [root at r1k1 ~] # Hi Kelly, Try running 'iostat -xdmc 1'. Look for a single drive that has substantially greater await than ~10msec. If all the drives except one are taking 6-8msec, but one is very

I am relatively new to R, so apologize up front for my long question, particularly if there is too much or too little information. I have a large time series data set where each subject's behavior was originally coded on .25s intervals for 3min task. I am trying to determine if the findings are different depending on the coding interval (i.e. Compare .25s to 1s to 5s to 10s). I also need to