similar to: Aggregate function for comparison stats

Hi, I have run into this problem a couple of times now and hope you can help! If I want to plot mulitiple series with differing x-axis values (however, all in the same range) in 1 plot with one common axis R obstruses the plots. E.g. if I plot water content against time and I start with the sampler at 5 cm depth, it plots that one right. But the next depth, 15 cm, is measured at slightly

Hi I am facing a problem where I would like to import a TIFF image (of spots on a nylon filter) into R (into a matrix for example). When plotting the matrix using fx. scatterplot3d I would then be able to see how the pixel-intensities are distributed in "spot-areas" on the filter - which would be very helpful. Does anynone know of a way to do this? Best regards, Peter Hagedorn ...

Dear List, Does anyone know how to simulate data from a GLM object correponding to values of the independent (x) variable that do not occur in the original dataset? I have tried using simulate(), but it generates a new value of the dependent variable corresponding to each of the original x-values, which is not what I need. Ideally I whould like to simulate new values for GLM objects

Hi, I am trying to create 3 mds plots: one with axis 1 vs axis 2, one with axis 2 vs axis 3, and one with axis 1 vs axis 3. When inputting my code, I only end up with one diagram and when inputting mdsg.mds$dims, the program returns 2 for 2 dimensions. How can I create the other two plots? Any help would be greatly appreciated, Calla Carbone The table I use is number of each taxa on each

Dear List I'm trying to run R on a DIGITAL Alpha / Linux RedHat 7.2 The .rpm requires libreadlin.so.4.1 RedHat 7.2 comes with libreadline.so.4.2 I installed the R-1.6.0-1.aplha.rpm with option --nodeps, since it otherwise complained that the required libreadline.so.4.1 was missing. This seemed to be the only unsatisfied dependency, at least that was the only one mentioned when installing

I have a data set something like this: "YYYY", "Value" 1972 , 117 1984 , 73 1969 , 92 1976 , 113 1999 , 80 1996 , 78 1976 , 98 1984 , 106 1976 , 99 it could be created with: > dafSamp <- data.frame(cbind(c(1972,1984,1969,1976,1999,1996,1976,1984,1976),c(117,73,92,113,80,78,98,106,99))) The real dataset is of cause much larger, app. 100.000 samples

Dear R-Help, I have used R2.6.0 until I recently installed also R2.7.2 (see details below) In R 2.6.0, the following script using the function 'var' (cor(stats)): x.test <- c(NA, NA, NA, NA) var(x.test, na.rm=T) gives the output: NA In R2.7.2 the output of the same script generates an error message and stops R: 'Error in var(x.test, na.rm = T)

Hello R-gurus, I'm trying to adjust different growth curves to a rather extensive dataset. I wrote up a function to go through all of them, but am encountering a problem : among the more than 1000 curves I have, obviously for some of them I encounter conversion problems. I'd like for my function to keep going to the next curve and store the fact that for curve number X I had a convergence

I'm a week-old R user, and have become stuck trying to create usable CSV outputs for post-processing. I am using the package Rioja, which provides small datasets of results. I am running several analyses in a loop and iteratively adding the results to a *list* ("combined"). Within each iteration I use the following: > combined[[i]] <- performance(fit) With two iterations I

Hello all, I use the arima to get a model, i.e. fit = arima(x,order=c(1,0,0)) and I know I can get the following from fit via est.coef = coef(fig) est.aic = fit$aic std.err = sqrt(diag(vcov(fit))) t.stat = est.coef/std.err How can I get the following stat from arima? Pr(>|t|) r2 adjust_r2 rmse Thanks, Rebecca

Dear Researches, I am using RF (in regression way) for analize several metrics extract from image. I am tuning RF setting a loop using different range of mtry, tree and nodesize using the lower value of MSE-OOB mtry from 1 to 5 nodesize from1 to 10 tree from 1 to 500 using this paper as refery Palmer, D. S., O'Boyle, N. M., Glen, R. C., & Mitchell, J. B. O. (2007). Random Forest Models

I ran into a problem with titles on graphs. I wanted a graph with multiple subplots, with each having a title that involved both a Greek letter and an identifier for each graph. Below is a simplified version of code to do this. The graph appears fine, with the first graph having "i=1" in the title, and the second graph having "i=2" in the title. However, when I resize the

Hola!! Estoy intentando evaluar mi modelo de series temporales (uso auto.arima). Para ello he implemetado el método "rolling window" que se basa en ir añadiendo progresivamente datos al conjunto de train para testar el modelo. Por ejemplo: - Train: 1 año, test: día 1 (24 observaciones, una por hora) --> evalúo ese día (RMSE por ejemplo) - Train: 1 año + 1 día, test: día 2 -->

I am new to R, can anyone help with boxplot for a dataset like: file1 col1 col2 col3 col4 col5 050350005 101 56.625 48.318 RED 051010002 106 50.625 46.990 GREEN 051190007 25 65.875 74.545 BLUE 051191002 246 52.875 57.070 RED 220050004 55 70 80.274 BLUE 220150008 75 67.750 62.749 RED 220170001 77 65.750 54.307 GREEN file2 col1 col2 col3 col4 col5 050350005 101 56.625 57 RED 051010002 106 50.625 77

Need Help in Debugging below script:-------------------------------- dat <- get_majorlandmarks(dat,Dmin,Per) fit_xts <- xts(dat$fit,order.by = dat$Date,frequency = 365) close_xts <- xts(dat$Close, order.by = dat$Date, frequency = 365 ) majorlandmarks_xts <-xts(dat$Close[dat$majorlandmarks==TRUE], order.by = dat$Date[dat$majorlandmarks==TRUE], frequency = 365 ) minorlandmarks_xts

Hi, I am doing predictive modelling of Multivariate Time series Data of a Motor in R using various models such as Arima, H2O.Randomforest, glmnet, lm and few other models. I created a function to select a model of our choice and do prediction. Model1 <- function(){ .. return() } Model2 <- function(){ ... return() } Model3 <- function(){ ... return() } main <-

Hi everyone, Can someone please help me in these questions?: 1)if I use crossvalidation with svm, do I have to use this equation to calculate RMSE?: mymodel <- svm(myformula,data=mydata,cross=10) sqrt(mean(mymodel$MSE)) But if I don’t use crossvalidation, I have to use the following to calculate RMSE: mymodel <- svm(myformula,data=mydata) mytest

I would like the text plotted with 'mtext' to be alighned like it is for printing on the console. Here is what I have: > print(emt) ME RMSE MAE MPE MAPE MASE original -1.034568e+07 1.097695e+08 2.433160e+07 -31.30554 37.47713 1.5100050 xreg 1.561235e+01 2.008599e+03 9.089473e+02 267.05490 280.66734

I just built a package in R (version 2.1.1 on a Linux machine) and then moved it to my computer (R version 2.8.1 on a Windows machine). When I loaded the package and tried to open help for one of the commands, I got the following warning: Warning message: In print.help_files_with_topic("F:/R/R-2.8.1/library/REEMtree/chm/RMSE") : No CHM help for 'RMSE' in package

I'm using 2.10.0 on Linux (64 bit), and I just noticed that random numbers are occasionally added to the text of names in vectors. It's happened to me in two separate, long-running R sessions, but I can't find a way to reproduce it in a smaller setting. The code I'm using is > diag.gam.2 <- mdl.run.diag(fit.gam.2, ds.valid) > diag.gam.2 rmse mdae.1413751