similar to: Iterated Data Input/Output with Random Forests

Hello, On a machine with CentOS-5.6, I need libvorbis >= 1.2, so I have recompiled and packaged libvorbis. But I get the following error : $ rpm -U /usr/src/redhat/RPMS/x86_64/libvorbis-1.2.3-phn.1.x86_64.rpm /usr/src/redhat/RPMS/x86_64/libvorbis-devel-1.2.3-phn.1.x86_64.rpm package libvorbis-1.1.2-3.el5_4.4.x86_64 (which is newer than libvorbis-1.2.3-phn.1.x86_64) is already

I am trying to run a partialPlot with Random Forest (as I have done many times before). First I run my forest... Cell is a 6 level factor that is the dependent variable - all other variables are predictors, most of these are factors as well. predCell<-randomForest(x=tempdata[-match("Cell",names(tempdata))],y=tempdata$Cell,importance=T) Then I try my partial plot to look at the

I have a dataFrame variable: L1 L2 L3 ... v1 v2 ... 1 2 3 4 ... I want to process subsets of it as defined by combinations of L1-L2-L3. I do it successfully using nested loops: for (i in valuesOfL1 { for (j in valuesOfL2) { for (k in valuesOfL3) { tempData <- subset(dataFrame, (L1 == i & L2 == j & L3 == k, select=c(v1,v2) )) if

Hi : I have old Splus code that I am trying to turn into R ( I am using windows Xp and R 2.20 ) and I am getting a warning from one of my statements because the behavior of R is different from Splus. below, tempdata is a matrix of numbers and I have the following command which basically runs through the columns and returns the minimum index of the column where an NA occurs.

hi everyone : i'm not sure if my previous mail about this got sent. i was typing and erroneosuyl hit a button and lost what i was typing. anyway, i have the code below ( it works ) in which i run through the rows of a dataframe, taking out the first two fields which are characters strings ( with some extra spacing so i yuse gsub) and appending these character strings to a list so that i can

Hi, Input Format: excel file (XLS) Column 1: Gene ID (alphanumeric) Column 2 - 10 : (numeric data). inData = read.xls ( <fileName>) geneLabel = inData [ , 1] - column 1 stored in geneLabel tempData = inData [ , 2: 10] expValues = data.matrix (tempData) - convert frame into Matrix format expValues has the matrix format needed for analysis. I need to bind gene labels as . I

Hello, Does anybody know if the outscale option of randomForest yields the standarized version of the outlier measure for each case? or the results are only the raw values. Also I have notice that this measure presents very high variability. I mean if I repeat the experiment I am getting very different values for this measure and it is hard to flag the outliers. This does not happen with two other

Dear all, I'm a new R user and I find myself in trouble with some of the plot functions. I'm trying to save a sequence of plots to eps files using a for loop, but I get only empty figures. In each iteration of the for loop I fit a nlme model and I'd like to plot its prediction of the dependent variable values. This is the code I'm using to plot the figures (I removed the commands I

Dear Gabor, Thanks for your reply. however: > tail(DJd) ^DJI.Close 2010-04-01 10927.07 2010-04-05 10973.55 2010-04-06 10969.99 2010-04-07 10897.52 2010-04-08 10927.07 *2010-04-09 10997.35* > tail(ag) 2009-11-30 10344.84 2009-12-31 10428.05 2010-01-31 10067.33 2010-02-28 10325.26 2010-03-31 10856.63 *2010-04-30 10997.35 * It seems the script "makes up"

Hello All, Recently developed the code below for graphing patterns of chemotherapy administration. As someone just starting to use R in their work, I managed to figure out some parts of the code but needed help with others. setwd("N:/Regimen Coding/0906/Plots Test") getwd() TestData <- structure(list(profile_key = c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3), line = c(1, 1,

Following problem: Say you have a bunch of parameters and want to produce results for all combinations of those: height<-c("high","low") width<-c("slim","wide") then what i used to do was something like this: l<-list() for(h in height){ l[[h]]<-list() for(w in width){ l[[h]][[w]] <- doSomething() } } Now those parameters aren't

Hi, I cant understand where I am going wrong.Below is my code.I would really appreciate your help. Thanks. > genfile<-read.table("c:/tina/phd/bs871/hw/genfile.txt",skip=1) > > #read in SNP data > snp.dat <- as.matrix(genfile) > snp.name <- scan("c:/tina/phd/bs871/hw/genfile.txt",nline=1,what="character") Read 100 items

# Here is the solution: require(fBasics) # Be sure that R is running in time zone GMT. # Set your Windows environment variable to "GMT" # Your PC Windows clock can still run in any other time zone! # My clock is now running in Zurich in Europe. Date = c("2003-10-09", "2003-10-10", "2003-10-13", "2003-10-14") Open = c(1.27, 1.25, 1.27,

Dear All, wonder if you have some thoughts on running the with() function (and perhaps including the pool() function to get the results?) in glmulti? In other words, how to run glmulti with a data set that is produced by mice()? publicly available code: data <- airquality data[4:10,3] <- rep(NA,7) data[1:5,4] <- NA data <- data[-c(5,6)] library(mice) library(glmulti) the following

As a national broadcaster, ISDN is definitely NOT cost effective compared to IP based transport. It does buy you reliable transport and reasonable delay however. For us to get to StarGuide and our affiliates, we have to use ISDN. We spend a lot of money on these lines and have driven our rate down to 4 cents per minute. But we DO NOT broadcast 24 hours a day. I would consider an ADN, Fract T1,

I have a matrix that looks like this: structure(c("0.0376673981759913", "0.111066500741386", "1", "1103", "18", "OPEN", "DEPR", "0.0404073656092023", "0.115186044704599", "1", "719", "18", "OPEN", "DEPR", "0.0665342096693433",

Hi. I?m trying to use the speex library in c#, everything seems to works right, when I call the speex_encode_int function it always return 0, any help would be appreciated. Here?s the sequence of calls: //Initialization _Mode = speex_lib_get_mode(0); _State = speex_encoder_init(_Mode); fixed (int* __FrameSize = &_FrameSize, __Complexity =

I have many "sample" datasets (e.g. sample 5, sample 6, etc), each identified by a number as a suffix. These datasets are saved as individual R objects on my hard drive. (e.g."Wind.5.r" . "Wind.6.r","Solar.5.r","Solar.6.r") For example purposes, I have written code that creates similar data files using the "airquality" dataset. (see

Hello list, Thank you very much for replying to my earlier questions. I have a few new questions about R plots: Example: tempdata: RDate Price 2009-12-09 12:00 100 2009-12-09 15:00 99 2009-12-09 18:00 102 .... 2009-12-10 8:00 120 2009-12-10 10:00 110 2009-12-10 16:00 105 My code: (RDate already in R date-time class) plot (price~RDate, data=tempdata, "l") axis.POSIXct(1,

i have a data matrix with some x variables complete and some y variables incomplete. i want to use the simplest regression imputation to fill in the missing data. (form a regression line with all complete cases and predict the missing values). is there any package that can do so? if not how should i write the code? -- View this message in context: