similar to: Avoiding for loop

Dear All, I would like to use the simprof function (clustsig package) but the available distances do not include Jaccard distance, which is the most appropriate for pres/abs community data. Here is the core of the function: > simprof function (data, num.expected = 1000, num.simulated = 999, method.cluster = "average", method.distance = "euclidean", method.transform =

Hi, I am trying to use piecewise linear regression to approximate a nonlinear function. Actually, I don't know how many linear functions I need, therefore, I want build an array of regression models to automate the approximation job. Could you please give me any clue? Attached is ongoing code: rawData = scan("c:/zyang/mass/data/A01/1.PRN", what=list(numeric(),numeric())); len =

Dear all, Let say I have following data: RawData <- matrix(1:101, nr = 1); colnames(RawData) <- c("ASD", as.character(as.yearmon(seq(as.Date("2012-03-01"), length.out = 100, by = "1 month")))); rownames(RawData) <- "XYZ" CutOffDate <- as.Date("2012-09-01") NewDateSeries <- as.character(as.yearmon(seq(CutOffDate, to =

In an earlier post, a person wanted to divide each of the rows of rawdata by the row vector sens so he did below but didn't like it and asked if there was a better solution. rawdata <- data.frame(rbind(c(1,2,2), c(4,5,6))) sens <- c(2,4,6) temp <- t(rawdata)/sens temp <- t(temp) print(temp) Gabor sent three other solutions and I understood 2 of them but not the

Dear R, I import data from spss into a R data.frame. On this rawdata I do some data processing (selection of observations, normalization, recoding of variables etc..). The result is stored in a new data.frame, however, in this new data.frame the value labels are lost. Example of what I do in code: # read raw data from spss rawdata <- read.spss("./data/T50937.SAV",

Hi R -users, i've a table as describe below. I'm reading the numeric value presented in this table to populate a list. #table #============ #X    A    B    C #x1    2    3    4 #x2    5    7    10 #x4    2    3    5 #============ rawData <- read.table("raw_data.txt",header=T, sep="\t") myList=list() counter=0 for (i in c(1:length(rawData$X))) {     print (i)    

Hello there, Much thanks in advance for any help. I have a few questions: 1) Why do I keep getting the following error: File1 <- read.csv("../RawData/File1.csv",as.is=TRUE,row.names=1) Error in file(file, "rt") : cannot open the connection In addition: Warning message: In file(file, "rt") : cannot open file '../RawData/File1.csv': No such file or

Hi All, I have txt file like : $ cat data.txt US 10 UK 12 Ind 4 Germany 14 France 8 > rawdata <- read.table(file='data.txt',sep='\t' , header=FALSE) > rawdata V1 V2 1 US 10 2 UK 12 3 Ind 4 4 Germany 14 5 France 8 I want to draw pie chart for the above data. How to split rawdata into : con <-

Hi, More questions in my ongoing quest to convert from RapidMiner to R. One thing has become VERY CLEAR: None of the issues I'm asking about here are addressed in RapidMiner. How it handles misisng values, scaling, etc. is hidden within the "black box". Using R is forcing me to take a much deeper look at my data and how my experiments are constructed. (That's a very

I am having a problem understanding the lda package. I have a dataset here: [,1] [,2] [,3] [1,] 2.95 6.63 0 [2,] 2.53 7.79 0 [3,] 3.57 5.65 0 [4,] 3.16 5.47 0 [5,] 2.58 4.46 1 [6,] 2.16 6.22 1 [7,] 3.27 3.52 1 If I do the following; "names(d)<-c("y","x1","x2") d$x1 = d$x1 * 100 d$x2 = d$x2 * 100 g<-lda( y ~ x1 + x2, data=d) v2

Hello, I'm wondering how I can merge two featuresets into one. My dataset is two sets of microarray data and it looks like followings: > rawData $v1 TilingFeatureSet (storageMode: lockedEnvironment) assayData: 2197815 features, 59 samples element names: channel1, channel2 protocolData rowNames: LT290677RU_D1_2011-02-16 LT286300LU_D1_2010-07-24 ... LT003990RU_D1_2010-11-04 (59

Hi everyone, I experience some problems with adressing of data.frames when I retrieve some information for geographical position (ypos, xpos) ot of a MySQL Database and want to perform some simple statistics. The problem is adressing the dataframes with a construct like rawdata[c(type)] vs. rawdata$TEMPMIN to retrieve the numerical information and not a string (I want to store the numerical

Hello, I am importing some raw voltage multichannel measurements into an R data frame. I need to scale each column with the respective sensitivity for that channel. I figured how to do it, but I am curious if there isn't a more elegant way. Now I start with something like this: rawdata <- data.frame(rbind(c(1,2,3), c(4,5,6))) sens <- c(2,4,6) and I do this: data <-

Hello, I call a function via .Call passing to it a raw vector(D) and an integer(I) The vector is a series K1,KData1, V1,VData1, K2, KData2, ... where the integer K1 is the length of Data1 and similarly for Ki (wrt Datai)(similarly for V*) There 2*I such pairs( (Ki,KDatai), (Vi,VDatai)) The numbers Ki(and Vi) are written in network order. I am returning a list of I elements each element a

Thanks David, Yes, I am talking about the MASS package.Thank you for pointing out that these scale the same. My question is, how do I get from the V1 data: V1 1 164.4283 2 166.2492 3 170.5232 4 156.5622 5 127.7540 6 136.7704 7 136.3436 to the other set of data: + 1 -2.3769280 + 2 -2.7049437 + 3 -3.4748309 + 4 -0.9599825 + 5 4.2293774 + 6 2.6052193 + 7 2.6820884 On Mon, Sep 28, 2009

Here's the small scale version of the R script: http://pastebin.com/sEYKv2Vv Here's the file that I'm reading in: http://r.789695.n4.nabble.com/file/n4487682/weatherData.txt weatherData.txt I apologize for the length of the data. I tried to cut it down to 12 lines, however, it wasn't reproducing the bad output that I wanted to show. The problem is that my whole data set

Hi, This should be an easy one, but I have some trouble formatting the data right I'm trying to replace the column of a subset of a dataframe with the scaled data for that column of the subset subset(rawdata, code== "foo", select = a) <- scale( subset(rawdata, code== "foo", select = a) ) It returns: could not find function "subset<-" The scale

R-users, I want to concatenate columns from different files in a single object. I'm doing bad. My peace of code is as follow: rawdata <- list.files("./data") for (i in rawdata) { mat[ ] <- read.table(paste(i ,sep="")) } At the end of the loop I have just one column. What I'm doing wrong? Thanks, Fred -- View this message in context:

I'm using xyplot in a very simple way---a scatter plot of several data sets. I'm having a problem getting auto.key to display different point characters. The following produces a plot that employes different colors, all with pch(1), for the different groups, with a matching key. xyplot(Force~Time, rawData, groups=Sample, panel = panel.superpose, auto.key=TRUE) The following

Dear R help I have conducted a fa() analysis, and I want to use fa.diagram to assess the extent to which the 11 latent factors predict the 37 items in a psychological battery. However, the display on the screen has very large font size for the coefficients of the relationship between the 11 factors and the 37 items, so the numbers overlap and are therefore illegible. When I output this to a