similar to: replacing with NA

Dear R users, I was wondering how I can convert a raster image (that made R through interpolation) into an ascii or csv format? this is the last line of my command p <- interpolate(r, tpsfit) So p is my raster file which I want to convert into ascii or csv Many thanks Regards Mintewab

Dear R users, I have now managed to fit the curve using the thin plate spline as follows: library(mgcv) b <- gam(y~s(x1,x2,k=100),data =dat) vis.gam(b) What I want now is to get the fitted data for y and copy it so that I use it for further analysis. Many thanks in advance mintewab

Dear R users, I am using the code below to generate a fitted value of b. I have about 300 different values for for y (y1, y2, ...y300) which means I will have to write the code below 300 times to generate the 300 different fitted values for y. Is there a short way of doing that ? Many thanks in advance Mintewab library(mgcv) dat <- read.table("e:/minti's

Dear R users, I am a beginner in R trying to apply the thin plate spline method to my climate data. I used the example in R to do so, and the lines seem to run fine ( I am not getting errors) but I am not getting any output in the form of graph or anything. I got a warning message saying that 'surface extends beyond box'. Any help is much appreciated. thanks minti

I may be doing this wrong! but I have a function which I have simplified a lot below. I want to pass some 'field names' of a data-frame to the function for it to then do some manipulation of. Here's my code: #build a simple dataset mydataset = data.frame (

Hi, I am performing a two-way ANOVA (2 factors with 4 and 5 levels, respectively). If I'm interpreting the output of summary correctly, then the interaction between both factors is significant: ,---- | ## Two-way ANOVA with possible interaction: | > model1 <- aov(log(y) ~ xForce*xVel, data=mydataset) | | > summary(model1) | Df Sum Sq Mean Sq F value Pr(>F) |

Hi list, I am using the capscale function in vegan_2.0-7 to do a constrained principal coordinates analysis, and I kept getting the following error message: Error in Y.r[, oo, drop = FALSE] : subscript out of bounds I googled but I couldn't find an answer. Could anyone tell me why this error msg and what to do? Here is the command I used:

Dear members of this list, I'd like to count missing values using the aggregate function. Something like this: count_nas <- function(arg1) { return(sum(is.na(arg1))) } aggregate(cbind(var1, var2, var3) ~ subject + time, data = mydataset, count_nas) It's not working: I end up with a matrix containing zeros, although there are missings in the data frame. I'd highly

Hello all, I have a peculiar and particular bug that I stumbled across with ggplot2. I cannot seem to replicate it with anything other than my specific data set. Here is the problem: - when I try to plot a histogram, allowing for ggplot2 to decide the binwidths itself, I get the following error: - stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to

Dear all, I'm trying to use the lattice barchart function to obtain a bar plot of a variable for different values of two factors. The thing I'm trying to do is something like this: > barchart(MyVar ~ season | place, data=mydataset) My problem is that the column MyVar has some negative values and I would like them to be represented as bars stacking down from zero instead of what

Dear R-friends, I use optim(par=c(mystartingpoints), fn=myloglikelihoodfunction, gr=NULL, method=c("L-BFGS-B"), ## I would like to do not use any bounds control=list(trace=6, ## just to see what it's going on maxit=c(20000)), ## to be sure the it doesn't stop reaching the max iterations

Hi there, I am having some trouble with the Identify() function, it looks that the identify() function only works on the plot of 2-dimension data set. In high-dimension case , if I use pairs() + identify() in hope to observe all the components of the data point I selected, I get error message. Is there anyway to get around this ? Plus, I also need it to actually compare all the

Hello, I want to start Klimt from S.Urbanek directly from R. In the description of klimt is the following R-Code: source("klimt.r"); d<-read.table("mydataset.txt"); t<-tree(OUT2~.,d); Klimt(t,d); One should make sure, that the klimt.jar is in the working directory of R (in my case "C:\Program FilesR\R-2.8.1" I think). But although I copied klimt.jar into

Good morning all. I am doing bagging with package caret. I need bagging for a classification problem. I am working with " bag". bag(x, y, B = 10, vars = NULL, bagControl = bagControl(), ...) bagControl(fit = NULL, predict = NULL, aggregate = NULL, downSample = FALSE) My fit function is: svmFit <- function(x, y, ...) { library(e1071)

I tried to post this a few times last week and it seems to have got stuck somehow so I'm trying from a different email in the hope that works. If somehow this has appeared on the list 20 tiems and I never saw any of them I apologize ;-) I'm basically an R-newbie. But I am VERY computer literate. But this has me stumped... All the examples for using the rmeta package to create a

Hi Bert, Below the information you asked me for: nrow(mydataset) [1] 2986276 ######## sapply(mydataset, "class") $`Transit Date` [1] "POSIXct" "POSIXt" $`Market Segment` [1] "character" $`N?mero de Tr?nsitos` [1] "numeric" $`Tar No` [1] "character" $`Beam Range (Operations)` [1] "character" $`Operational Vessel Ranges

Hi all, A short while ago I asked a question about multiple imputation and I got several helpful replies, thanks! I have untill now tried to use the packages mice and norm but both give me errors however. mice does not even run to start with and gives me the following error right away: iter imp variable 1 1 Liquidity.ratioError in chol((v + t(v))/2) : the leading minor of order 1 is not

Dear wizaRds, I have a dataset to analyse which is causing me problems. It is a sample of parents in schools. First we had a population table of the schools in the country in question divided into five regions, and in each region we have an urban/rural split. The population Ns in these ten cells are known. Then three schools were drawn from each cell according to the Lahirie method, i.e with

Hey R-users, I think I followed the steps but still couldn't figure this out.. I am creating a personal package and I want to include several datasets in the package. I created a subdirectory 'data' in the package, save a dataset 'test.rda' there, built the package, checked it, installed it. Then I loaded the package and tried load(test), data(test), attach(test), none of them

Dear R-helpers, In my dataset I have two continuous variable (A and B) and one factor. I'm investigating the regression between the two variables usign the command lm(A ~ B, ...) but now I want to know the regression coefficient (r2) of A vs. B for every factors. I know that I can obtain this information with excel, but the factor have 68 levels...maybe [r] have a useful command. Thanks,