similar to: Memory problem

I have a quick question which is very simple but I seem to have a mental block! I'm using the pchisq function to specify a Chi Squared distribution with 9 df which I'm then going to use in the Kolmogorov-Smirnov Test to test some simulated values. so simply: pchisq(q, df=9) I know that q is the vector of quantiles but could anybody tell me what exactly this vector needs to contain?

Dear list I have a vector of values that allegedly have a chi-squared distribution. I want to create a plot that shows the values I have obtained, and the chi-squared distribution curve for the specified number of degrees of freedom to show what should have been obtained. At the moment I am plotting the values I have obtained as a histogram and somehow want to put on to this plot the

Dear list I have a quick question which is probably very simple. I have a data frame, and want to sort the data by putting one column in to ascending order i.e becomes A B A B 1 0.5 3 0.4 2 0.9 1 0.5 3 0.4 4 0.7 4 0.7 2 0.9 I can't seem to find anything in the help about sorting data

Dear list I have a very simple question which is causing me problems! I have a matrix A and simply want to rbind this matrix together n times (n is a large number) How can I write this in R? I know I could do new<-rbind(z,z,z,...z) with z written n times but this will take forever as n is so large. Is there a simple way to write this? Cheers Mick

Dear list I am using the qq.plot command to create quantile-quantile plots. The plot should display a 45 degree reference line upon which the points of the graph should fall if the two distributions being examined are roughly equal. If I try: x<-rchisq(100, df=6) qq.plot(x, dist="chisq", df=6) Then I get a quantile plot which has an intercept of roughly 1 when the line should be

Dear list I am having a couple of problems with the package 'bindata'. Having installed it using install.packages("bindata"), I am finding that when I load it up as a library I get the following errors: > library(bindata) Loading required package: e1071 Loading required package: mvtnorm Warning messages: 1: There is no package called `e1071' in: library(package, char

Dear list I have a simple question that I have a mental block on: Having used a loop (from i = 1 to n) to assign some numerical values to row.list[[i]] e.g. row.list[[3]]= 0 1 I am wanting to combine the output into a simple matrix. for example, if I combine the output from persons 1 to 3 into a matrix, I thought I could do : h<-rbind(row.list[[1]]:row.list[[3]]) However, I get the

Dear List I am having a bit of a problem getting a program to work. For each of i=1 to n persons I have a matrix (different for each person) with m rows. What I want to do, is create m new data sets such that the first is made up of the first row for each person from the original matrices, the second contains the second row for each person from the original matrices etc etc up to the mth

Hi All, I have a 1000x1000000 matrix. The calculation I would like to do is actually very simple: for each row, calculate the frequency of a given pattern. For example, a toy dataset is as follows. Col1 Col2 Col3 Col4 01 02 02 00 => Freq of ?02? is 0.5 02 02 02 01 => Freq of ?02? is 0.75 00 02 01 01 ? My code is quite simple as the following to find the pattern ?02?.

Hi, I have huge matrices in which the response variable is in the first column and the regressors are in the other columns. What I wanted to do now is something like this: #this is just to get an example-matrix DataMatrix <- rep(1,1000); Disturbance <- rnorm(900); DataMatrix[101:1000] <- DataMatrix[101:1000]+Disturbance; DataMatrix <- matrix(DataMatrix,ncol=10,nrow=100); #estimate

Hello R users, I'm wondering whether it is possible to manage big data set in R? I have a data set with 3 million rows and 3 columns (X,Y,Z), where X is the group id. For each X, I need to run 2 regression on the submatrix. I used the function "split": datamatrix<-read.csv("datas.csv", header=F, sep=",") dim(datamatrix) # [1] 2980523 3

Hi, I need to permute the rows of a matrix, where each row is independently rearranged. A simple solution is this: shuffled <- datamatrix <- matrix(1:24, ncol = 4) for (i in 1:nrow(datamatrix)) { shuffled[i, ] <- sample(datamatrix[i, ]) } > datamatrix [,1] [,2] [,3] [,4] [1,] 1 7 13 19 [2,] 2 8 14 20 [3,] 3 9 15 21 [4,] 4 10 16 22 [5,]

In datamatrix[, "y"] == datamatrix[, "y"][-1] : longer object length is not a multiple of shorter object length out = c(FALSE,datamatrix[,'y'] == datamatrix[,'y'][-1]) and I do not know why I get that error, the resulting out matrix is somehow one row larger than datamatrix... all I try to do is filter matrix by dropping rows where [,'y'][-1] ==

Hi. I have been looking at the PCAproj function in package pcaPP (R 2.4.1) for robust principal components, and I'm trying to interpret the results. I started with a data matrix of dimensions RxC (R is the number of rows / observations, C the number of columns / variables). PCAproj returns a list of class princomp, similar to the output of the function princomp. In a case where I can

Hi list, I'm performing a series of confirmatory factor analysis on different groupings of items from data collected with questionnaires. There are some missing values. For those sets with no missing values I call factanal(datamatrix,factors=n) where datamatrix is a table of all observations for the items under investigation. This call fails when there are missing values. help(factanal)

Hi, Here in R, I need to load a huge file(.csv) , its size is 200MB. [may come more than 1GB sometimes]. When i tried to load into a variable it taking too much of time and after that when i do cbind by groups, getting an error like this " Error: cannot allocate vector of size 82.4 Mb " My requirement is, spilt data from Huge-size-file(.csv) to no. of small csv files. Here i will give

I'm a beginner in R and, therefore, I don't know how serious my trouble is. After running a script: ** *t**<-c(14598417794,649693)* *data**=data.frame(read.spss("C:\\Ginters\\Kalibracija\\cal_data.sav"))* *Xs=**as.matrix(data[,1:2]) * *koef**=data.frame(read.spss("C:\\Ginters\\Kalibracija\\f.sav")) * *piks=**as.matrix(koef[,1**])*

Hello R users, I'm trying to replace numerical values in a datamatrix with strings. R does this except for numbers under 10000 starting with a 9 (eg 98, 970, 9504 etc). This is really weird and I wondered whether someone had encountered such a problem or knows the solution. I'm using the next script: test_1 <- read.table("5+ref_151111clusters3.csv", header = TRUE, sep =

Hi all, I am wandering.. is it possible to cluster data which is in a single column ? for example.. I have some data as follows: 4013 7362 7585 9304 11879 14785 21795 30500 30669 30924 33988 36975 40422 42911 50501 51593 53729 54338 55497 57337 61993 62601 66229 69815 69933 70760 71340 75921 83972 90134 91061 . . . is it possible to cluster this data since it is in a single column ? I have

Dear All: I tried to use heatmap.2 to generate hierarchical clustering using the following command: heatmap.2(datamatrix, scale="row", trace="none", col=greenred(256), labRow=genelist[,1], margins=c(10,10), Rowv=TRUE, Colv=TRUE) datamatrix is subset of a RMA normalized data subset by a genelist. The problem is a lot of times, the z-score in key are from, like -5 to 15 or