similar to: loess crash

Dear All, I am new to R, I have one question which might be easy. I have a large data with more than 250 variable, i am reducing number of variables by redun function as in the example below, n <- 100 x1 <- runif(n) x2 <- runif(n) x3 <- x1 + x2 + runif(n)/10 x4 <- x1 + x2 + x3 + runif(n)/10 x5 <- factor(sample(c('a','b','c'),n,replace=TRUE)) x6 <-

Dear All, I have got the limits for removing extreme values for each variables using following function . f=function(x){quantile(x, c(0.25, 0.75),na.rm = TRUE) - matrix(IQR(x,na.rm = TRUE) * c(1.5), nrow = 1) %*% c(-1, 1)} #Example: n <- 100 x1 <- runif(n) x2 <- runif(n) x3 <- x1 + x2 + runif(n)/10 x4 <- x1 + x2 + x3 + runif(n)/10 x5 <-

Hi, You might need to check library(boot).? I have never used that before.? So, I can't comment much.? It is better to post on R-help list.? I had seen your postings on Nabble in the past.? Unfortunately those postings were not accepted in R-help.? You have to directly post at ? r-help at r-project.org after registering at: https://stat.ethz.ch/mailman/listinfo/r-help ?

When data contains both factor and numeric variables, how to get quartiles for all numeric variables? n <- 100 x1 <- runif(n) x2 <- runif(n) x3 <- x1 + x2 + runif(n)/10 x4 <- x1 + x2 + x3 + runif(n)/10 x5 <- factor(sample(c('a','b','c'),n,replace=TRUE)) x6 <- factor(1*(x5=='a' | x5=='c')) data1 <- cbind(x1,x2,x3,x4,x5,x6) data

Hi all, I have the following x1<-paste("A", 1:6, sep = "") x2<- round(rgamma(6,2,1)) x3<-paste("B", 1:6, sep = "") x4<- round(rgamma(6,2,1)) data1 <- data.frame(x1,x2,x3,x4) I would like to get data2 <- c(A1=4, A2=1, A3=0,...) Is there any standard for such a case? Thank you very much in advance, Diego

Hi Experts, I am new to R, using following sample code for capping outliers using percentile information. Working on large data (30000 observations and 150 variables), loop I am using in the below mentioned code for detecting outliers and capping to upper /lower percentile value is taking much time for the execution. Is there anything wrong with code, can anyone suggest improvement in the script

Dear R-users I would like to apply classification and regression tree(CART) to the following data. I have some question on using 'tree' package. The data contains one response variable Y and five explanatory variables. The explanatory variable "x2" is categorical and not ordinal. But, the result obtained after running following R code has indicated that x2 is regard as

Hi R community, I'm running R 2.7.2 on Windows XP SP2. I'm trying to (1) plot loess lines for each of my groupings using the same color for each group; (2) plot loess predicted values. The first part is easy: data1 <- data.frame(Names=c(rep("Jon",9),rep("Karl",9)),Measurements=c(2,4,16,25,36,49,64,81,100,1,2,5,12,17,21,45,54,67),PlotAt=c(1:9,1:9)) data2 <-

Dear R users/developers I requested help to solve the problem of formulating Multivariate Sample selection model by using Full Information Maximum Likelihood (FIML)estimation method. I could not get any response. I formulated the following code of FIML to analyse univariate sample selection problem. Would you please advise me where is my problem library (sem) library(nrmlepln) Selection

I R-helpers #I have a data panel of thousands of firms, by year and industry and #one dummy variable that separates the firms in two categories: 1 if the firm have an auditor; 0 if not #and another variable the represents the firm dimension (total assets in thousand of euros) #I need to create two separated samples with the same number os firms where #one firm in the first have a corresponding

If I have a model line = lm(y~x1) and I want to use a for loop to change the number of explanatory variables, how would I do this? So for example I want to store the model objects in a list. model1 = lm(y~x1) model2 = lm(y~x1+x2) model3 = lm(y~x1+x2+x3) model4 = lm(y~x1+x2+x3+x4) model5 = lm(y~x1+x2+x3+x4+x5)... model10. model_function = function(x){ for(i in 1:x) { } If x =1, then the list

Hi Ruser As so usual I'm trying to replicate some SAS code. I wold like to know if there is a wildcard operators, as " : " in SAS, in R? When running: lm(y ~ x1 + x2 + x3 + x4 + x5 + x6 .... x9860, data=mydata) I would like to be able to get around it by just writing something like this: lm(y ~ x1:x9860, data=mydata) Anyone? Sorry for no including a working example, but I

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Hi R-helpers, I have a list containing 10 elements, each of which is a dataframe. I wish to add a new column to each list element (dataframe) containing the product of the last two columns of each dataframe. I'd appreciate any pointers, thanks! Mark Na [[alternative HTML version deleted]]

Dear R-dev, I would like to accelerate my R computation by using parallel OpenMP compilers (e.g from Pathscale) on a 2-processor AMD server and I would like to know whether R is a tread safe library. The main kernel of the OpenMP parallelization is a C SEXP function that performs the computational routine in parallel with: ******************* SEXP example(SEXP list, SEXP expr, SEXP rho) {

Hello All, Many thanks to the help I have received so far. Here is an example data set I hope to plot Data1 Year Data SE 1 2005 2 0.01 2 2006 4 0.01 3 2007 5 0.01 4 2008 2 0.01 5 2009 3 0.01 6 2010 6 0.01 Data2 Year Data SE 1 2006 32 1 2 2007 100 2 3 2008 60 4 4 2009 67 3 5 2010 8 1 Notice Data2 has one less years worth of data than Data1 (which is my

I have a sparse contingency table (most cells are 0): > xtabs(~.,data[,idx:(idx+4)]) , , x3 = 1, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 31 2 0 0 112 3 0 0 94 , , x3 = 2, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 0 2 0 0 0 3 0 0 0 , , x3 = 3, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 0 2 0 0 0 3 0 0 0 , , x3 = 1, x4

Hello R community, I am trying to combine two CSV files that look like this: File A Row_ID_CR, Data1, Data2, Data3 1, aa, bb, cc 2, dd, ee, ff File B Row_ID_N, Src_Row_ID, DataN1 1a, 1, This is comment 1 2a, 1, This is comment 2 3a,

Hola: Como dice Carlos, algo así, por ejemplo: transforma <- function(df) sapply(df, function(x) ifelse(x%in%c("x1","x2","x3"), "prueba1",ifelse(x%in%c("x4","x5","x6"),"prueba2",x))) > transforma(df1)       col1  [1,] "prueba1"  [2,] "prueba1"  [3,] "x11"  [4,]

Hi This question is far less simple than the title suggests, please read carefully, thanks. I have 2 sets of data, both read into R >data1<-read.table ("1.txt", header=T, sep="\t") >data2<-read.table ("2.txt", header=T, sep="\t") >data1 Taxon stage1 stage2 stage3 stage4 T1 0 0 1 1 T2 0