similar to: function to reduce resolution of a vector or matrix?

Hi, I would like to sum some specific columns in my matrix- for example, my matrix looks like this: [,1] [,2] [,3] [,4] [,5] [1,] 1 NA NA NA NA [2,] 2 1 NA 1 NA [3,] 3 2 1 2 1 [4,] 4 3 2 3 2 [5,] NA NA NA 4 3 [6,] NA NA NA 5 NA I would like to find the sum of the first two columns, the second two columns and

There are indeed speed advantages in using colSums etc. However the disadvantage is that the newbie doesn't always find the power inherent in the apply, sapply, tapply and mapply. For many things that I do, the speed is the least of my worries; although I take the point that using apply for means or sums in packages that are distibuted to others is not the way to go. As many of us have found

Dear list, I just made a very simple mistake, but it was hard to spot. And I think that I should warn other people, because it is probably so simple to make... === R code === # Let us create a matrix: (a <- cbind(c(0,1,1), rep(1,3))) # [,1] [,2] # [1,] 0 1 # [2,] 1 1 # [3,] 1 1 # That is a MISTAKE: a/colSums(a) # [,1] [,2] # [1,] 0.0000000 0.3333333

One problem I've been having is the special case in which only one row/column remains and the variable gets converted into a vector when entries are removed by logical masking. This is a problem because subsequent code may rely on matrix operations (apply, colsums, dim, etc) For example: > a <- matrix(c(1, 2, 3, 4), nrow = 2) > a [,1] [,2] [1,] 1 3 [2,] 2 4 >

Hello, I am using tapply to pull out data by the day of week and then perform functions (e.g. mean). I would like to have the number of values used for the calcuation for the functions, sorted by each day of week. A number of entries in any given column are NAs. I have tried the following code and simple variants with no luck. for (i in 1:length(a[1,])){ x<-tapply(a[,i],a[,1],mean,

Hi, I have a matrix, say m=matrix(c( 983,679,134, 383,416,84, 2892,2625,570 ),nrow=3 ) i can find its row/col sum by rowSums(m) colSums(m) How do I divide each row/column by its rowSum/colSums and still return in the matrix form? (i.e. the new rowSums/colSums =1) Thanks. Casper -- View this message in context:

Hi, I'd like to simply add column-wise using Matrix objects (Csparse). It looks like one can apply mosty any base function to these objects (i.e., apply, colSums), but there is a nasty conversion to traditional matrix objects if one does that. Is there any workaround? I can see colSum listed in the help for Class 'CsparseMatrix' , but I wonder whether I'm using the default

Hello, I am trying to filter a data set like below so that the peaks in the Phase value are more obvious and can be identified by a peak finding function following the useful advise of Carl Witthoft. I have written the following for(i in length(data$Phase)){ newphase=if(abs(data$Phase[i+1]-data$Phase[i])>6){ data$Phase[i+1] }else{data$Phase[i] } } I get the following error which I have not

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, Thanks in advance for any help. I have a square matrix of measures of interactions among individuals and would like to calculate a values from a function (colSums for example) with a single individual (row) excluded in each instance. That individual would be returned to the matrix before the next is removed and the function recalculated. I can do this by hand removing rows based upon

Hi, subject more or less says it all. I freely admit to not having bothered to find some of the online papers about method of testing the quality of random number generators -- but in an idle moment I wondered what to expect from something like the following: randa<-runif(1000) randb<-runif(1000) t.test(randa,randb)$p.value var.test(randa,randb)$p.value [repeat ad nauseum] Is the

Hi, A recent thread provided a (working) construct for lm: lm(as.matrix(freeny[ix]) ~., freeny[-ix]) Can someone explain what is meant by the formula in that expression, that is, what does "mymatrix~." do? I couldn't find any such example in the lm() or formula() help pages. thanks Carl

I want to create a randomly generated 25*15 binary matrix knowing what the colSums and rowSums of this matrix should be. colSums(a) [1] 3 7 2 5 0 4 6 5 5 4 3 4 4 5... rowSums(a) [1] 8 6 6 6 6 6 5 5 5 5 4 4 4... . . Baptiste Coulmont coulmont at yahoo.com --------

Hi all, I would like to know how can I sort the cols of a matrix by the sum of their elements. a <- matrix(as.integer(rnorm(25,4,2)),10,5) colnames(a) = c("alfa","bravo","charlie","delta","echo") I guess I should use colSums, and then rearrange the matrix somehow according to the result. My idea is to display a "sorted" barplot:

This is not the same as the recent thread on a waterfall graph. I'm thinking about the rolling FFT display used in acoustics and other spectrum analysis tasks. Here's an example of a very fancy 3-D waterfall display: http://www.ultimaserial.com/UltimaWaterfall.html I was just wondering if there are any simple hidden-line tools in R that I could use to draw simple waterfall displays.

Let's say I have, for some reason, a bunch of scalars (i.e. single-valued variables) and I want to merge them all into a single vector of values. Can someone recommend a better function, or simpler way, to do so than the following? Suppose my scalars' names are foo1, foo2, foo3, foo1high, foo2high, foo3lo2, etc. Then I can do: >ls(pat='foo')->thels

Hello everybody, Without any loop and any package, I would like to return N products of M rows in a matrix A : Today, I managed to do it with a loop : B <- matrix(NA, ncol = ncol(A), nrow = 0) for (i in 1 : N) B <- rbind(B, apply(A[sample(1 : nrow(A), M, replace = T), ], 2, prod)) Do you have a solution ? Thank you in advance ! [[alternative HTML version deleted]]

Hi, So far as I can tell, the 'col.ticks' parameter for axis() only uses the first value provided. E.g.: plot(0:1,0:1, col.ticks=c('blue','red','green')) #all ticks are blue Just wondering if there's a different option in the basic plot commands that can handle multiple colors, and also whether ggplot and/or lattice allow for multiple tick colors.

Hi, While playing with quantile-quantile plots, I wrote up some code which plots something strangely different. Here's the pseudocode: testhist <- hist(sample_data) refhist <- hist(rnorm(n, mean=0,sd=1)) # for some large-ish n cumtest <- cumsum(testhist) cumref <- cumsum(refhist) plot(cumref,cumtest) This produces a straight line of slope 1 for a sample with the same

Hi, Sorry to bother with something that should be simple, but I can't find it. Suppose I have a list, each element of which is a 2xN dataframe, where N could be different for each element. Is there some simple structure to let me examine all the elements of each element's first column? For example: >foo $first [,1] [,2] [1,] 1 4 [2,] 2 5 [3,] 3 6 $second