similar to: Matching vector order by indicators in a matrix

Hi, Here i have a matrix like this, OLDMatrix <- X1 X2 X3 ----- ------ ------ 22 24 23 25 27 27 10 13 15 the thing is, im running two function(SUM,COUNT) to get output in another matrix called NEWMatrix NEWMatrix <- c("SUM",colSums(OLDMatrix )) NEWMatrix <- c("COUNT",colSums(!is.na(OLDMatrix

Dear all, i am stuck with a syntax problem. i have a matrix which has about 500 rows and 6 columns. now i want to kick some data out. i want create a new matrix which is basically the old one except for all entries which have a 4 in the 5 column AND a 1 in the 6th column. i tried the following but couldn´t get a new matrix, just some wierd errors:

Hello, I am sure I am not the only person with this problem. I have a list with n elements, each consisting of a single column matrix with different row lengths. Each row has a name ranging from A to E. Here is an example: alph[[1]] A 1 B 2 C 3 D 4 alph[[2]] A 1 C 3 D 4 alph[[3]] A 1 D 4 E 5 I would like to create a matrix from the elements in the list with n columns such that the row names

Hi when I fit a glm by glm.fit(x,y,family = binomial()) and then try to use the object for prediction of newdata by: predict.glm(object, newdata) I get the error: Error in terms.default(object) : no terms component I know I can use glm() and a formula, but for my case I prefer glm.fit(x,y)... thanks for a hint christoph $platform [1] "i686-pc-linux-gnu" $arch [1]

This will start off sounding very easy, but I think it will be very complicated. Let's say that I have a matrix, which shows the number of apples that each person in a group has. OriginalMatrix<-matrix(c(2,3,5,4,6),nrow=5,ncol=1,byrow=T,dimnames=list(c("Bob","Frank","Joe","Jim","David"),c("Apples"))) Apples Bob 2

I have been trying to copy the row names of one matrix to another matrix but having difficulty. The original matrix contains a row name which I would like to replicate in the new matrix. I use the following approach? The two matrices have identical dimensions. rN <- row.names(origMatrix) row.names(newMatrix) <- rN However the new matrix does not take on the labels. I have also tried,

Hi all, I need to replace missing values in a matrix by 10 % of the lowest available value in the matrix. I've got a function I've used earlier to replace negative values by the lowest value, in a data frame, but I'm not sure how to modify it... nonNeg = as.data.frame(apply(orig.df, 2, function(col) # Change negative values to a small value, close to zero { min.val =

Dear all, given I have data in a data.frame which indicate the number of people in a specific year at a specific age: n <- 10 mydf <- data.frame(yr=sample(1:10, size=n, replace=FALSE), age=sample(1:12, size=n, replace=FALSE), no=sample(1:10, size=n, replace=FALSE)) Now I would like to make a matrix with (in this simple example) 10 columns (for the

R offers a bewildering array of options when it comes to representing dates and times (e.g, as.Date, chron, strptime, zoo, etc). Can anybody recommend a document that compares the relative merit of each method? I'm not looking for help with any one method, but rather a guide that describes which method is best for a particular data analysis/plotting goal. Thanks, Jake [[alternative

Dear R-users I need to convert a matrix with three columns in a new array with multiple columns. For example, oldmatrix 1 4 5 1 54 52 1 9 43 2 32 5 2 54 6 2 76 6 3 54 54 3 543 7 3 54 6 newmatrix 5 5 54 52 6 7 43 6 6 if the first column have a new value then add a column to the new matrix and the new[i,j] <- old[,3][i] I write this code, but my initial matrix is very

Hello, I would like to write a loop to 1) run 100 linear regressions, and 2) compile the slopes of all regression into one vector. Sample input data are: y1<-rnorm(100, mean=0.01, sd=0.001) y2<-rnorm(100, mean=0.1, sd=0.01) x<-(c(10,400)) #I have gotten this far with the loop for (i in 1:100) { #create the linear model for each data set model1<-lm(c(y1[i],y2[i])~x)

Dear R-helpers, I'm trying to associate linear coefficients (intercept and slope) to tens of thousands of observations based on a table with benchmark values. #####Example - Value table and their corresponding coefficients (intercept and slope) coef = data.frame(cbind(st=c(1:5),b = runif(5,0.3,5),a = seq(0.5,5,1)))print(coef) #Example of observations to be computedobs = runif(20,1,5)print(obs)

I am currently a new asterisk user and new to telephony in general. I have been looking around to implement a solution with asterisk that has many of the nice features of a proprietary PBX for a small office. The features that I am looking for that I haven't been able to find any information on are: - status light indicators for which incoming line in ringing - status light indicators for

Hi all~ I am wondering if it is possible to alter the stopping precision for parameters estimated using the 'optim'? If it helps, I am minimizing the log-likelihood of a function using constraints (i.e. L-BFG-S). -Jeremy

Hi all, I try to write a simple function in a script. The script is as follows yo<-function(Xdata) { n<-length(Xdata[,1]) Lgm<-nls(formula=LgmFormula, data=Xdata, start=list(a=1500,b=0.1),weights=Xdata$Qe) return(Lgm) } After the execution of the script, when I call the function yo on data called NC60.DATA I get an error. #yo(NC60.DATA) Erreur dans eval(expr, envir, enclos)

Hi, I'm sometimes getting a failure of connecting 2 nodes when Tinc is started and configured in a LAN. In the logs, there are some unexpected dropped packets with very high or negative seq. I can reproduce this issue ~2% of the time. When this happens, the 2 nodes can no longer ping or ssh each other through the tunnel interface but using eth0 works fine. The connection can recover after at

Cipher is enabled with the default setting (Blowfish CBC) Digest is disabled Compression is disabled MACLength is the default (4 if I remember correctly) I suspect that the issue is related to the encryption. I tried disabling encryption and the issue wasn?t reproduced during an automated test run of 400 reconnections. Regards, Alexandre Beaulieu > On Nov 22, 2014, at 3:19 PM, Guus Sliepen

Hello R users, I'm a newby to R (and programming software at large) and I would need some help to sum up event data at discreet time and irregular time interval into a hourly frequency. Here is an example of my time series frame (irregular time-serie object - irts in the tseries package): time value 2008-12-19 19:11:03 GMT 1 2008-12-19 19:12:00 GMT 0 2008-12-19

Hi together I'm pretty new to R, so excuse me if it is a basic question. I have a big dataset (extract of it found in the attachment) of returns from firms. I'd like to compute the Pearson correlation of each firm with the "Market" and the corresponding p-Value. So I thought of making a list of 'cor.test's and then extract the needed values with a for loop. What I did so

Hi, Parameters assessment in R with nls doesn't work, though it works fine with MS Excel with the internal solver :( I use nls in R to determine two parameters (a,b) from experimental data. m V C0 Ce Qe 1 0.0911 0.0021740 3987.581 27.11637 94.51206 2 0.0911 0.0021740 3987.581 27.41915 94.50484 3 0.0911 0.0021740 3987.581 27.89362