similar to: conditional rowsums in sapply

Hi, I'm using colSums and rowSums to sum the first dimensions of arrays. It works ok but the resulting object is different. See > a3d <- array(rnorm(120, mean=2), dim=c(20,6,1)) > dim(colSums(a3d)) [1] 6 1 > dim(rowSums(a3d)) NULL > class(colSums(a3d)) [1] "matrix" > class(rowSums(a3d)) [1] "numeric" I was expecting rowSums to preserve the array

Working with an NxMxO sized matrix, currently I can do this in my code: if (max(colSums(array)) >= number) But to get an equivalent result using rowSums, I have to do: for (i in 1:10) { if (max(rowSums(array[,,i])) >= number) } I'm running both in a much larger loop that loops millions of times, so speed and such is quite a big factor for me. Currently, the colSums line uses about

Hi [R-2.6.0, macOSX 10.4.10]. The helppage says that rowSums() and colSums() are equivalent to 'apply' with 'FUN = sum'. But I came across this: > a <- matrix(1:30,5,6) > is.integer(apply(a,1,sum)) [1] TRUE > is.integer(rowSums(a)) [1] FALSE > so rowSums() returns a float. Why is this? -- Robin Hankin Uncertainty Analyst National Oceanography Centre,

I have a question on RowSums. Lets say i have a timeSeries table A B C 1/1/90 NA 1 1 1/2/90 NA 1 1 1/3/90 NA 1 1 1/4/90 NA 1 1 1/5/90 1 1 1 1/6/90 1 1 1 if i use RowSums, i will get 1/5/90 3 1/6/90 3 but i want 1/1/90 2 1/2/90 2 1/3/90 2 1/4/90 2 1/5/90 3 1/6/90 3 I cant

Hi R-users, I have a list a <- list(one=matrix(rnorm(20), 5, 4), two=matrix(rnorm(20, 3, 0.5),5,4)) How to add rowSums (calculated using lapply) to corresponding matrix in this list lapply(a, function(x) rowSums(x)) ?? -Lauri

Say I have the following data: testDat <- data.frame(A = c(1,NA,3), B = c(NA, NA, 3)) > testDat A B 1 1 NA 2 NA NA 3 3 3 rowsums() with na.rm=TRUE generates the following, which is not desired: > rowSums(testDat[, c('A', 'B')], na.rm=T) [1] 1 0 6 rowsums() with na.rm=F generates the following, which is also not desired: > rowSums(testDat[, c('A',

Dear R-help community, If I have a data.frame df as follows: > df x1 x2 x3 x4 x5 x6 1 5 5 1 1 2 1 2 5 5 5 5 1 5 3 1 5 5 5 5 5 4 5 5 1 4 5 5 5 5 1 5 2 4 1 6 5 1 5 4 5 1 7 5 1 5 4 4 5 8 5 1 1 1 1 5 9 1 5 1 1 2 5 10 5 1 5 4 5 5 11 1 5 5 2 1 1 12 5 5 5 4 4 1 13 1 5 1 4 4 1 14 1 1 5 4 5 5 15 1 5 5 4

This seems like it should be simple but I can't get it to work properly. I'm starting with a data frame like this: Tract Pct Totpop 1 0.05 4000 2 0.03 3500 3 0.01 4500 4 0.12 4100 5 0.21 3900 6 0.04 4250 7 0.07 5100 8 0.09

Greetings, My goal is to create a Markov transition matrix (probability of moving from one state to another) with the 'highest traffic' portion of the matrix occupying the top-left section. Consider the following sample: inputData <- c( c(5, 3, 1, 6, 7), c(9, 7, 3, 10, 11), c(1, 2, 3, 4, 5), c(2, 4, 6, 8, 10), c(9, 5, 2, 1, 1) ) MAT <- matrix(inputData,

Well, here's one way to do it: (dat is your example data frame) Cutoff <- seq(0, .15, .01) Pop <- with(dat, sapply(Cutoff, \(p)sum(Totpop[Pct >= p]))) I think there must be a more efficient way to do it with cumsum(), though. Cheers, Bert On Sat, Oct 14, 2023 at 12:53?AM Jason Stout, M.D. <jason.stout at duke.edu> wrote: > > This seems like it should be simple but I

Hi I am trying to calculate the row sums of a matrix i have created The matrix ( FeaturePresenceMatrix) has been created by 1) Read csv 2) Removing unnecesarry data using [-1:4,] command 3) replacing all the NA values with as.numeric(0) and all others with as.numeric (1) When I carry out the command TotalFeature <- rowrowSums(FeaturePresenceMatrix, na.rm = TRUE) I get the following

I'm having a very frustrating problem, trying to find the inverse distance squared weighted interpolants of some weather data. I have a data frame of weights, which sum to 1. I have attached the weights data. I also have a data frame of temperatures at 48 grid points, which I have also attached. Now, all I need to do is multiply all of the rows of the temperature data frame by the weights

Hello I would appreciate your help on the followig. I want to generate random binary matrices but I need to discard those with all-1 rows. That is, for a 10x10 matrix with five 1's [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 0 0 0 0 0 0 0 0 0 1 [2,] 0 0 0 0 0 0 1 0 0 0 [3,] 0 0 0 0 0 0 1

dear R-tists, i am experiencing a problem with the data editor in the windows version of R 1.6.1 envoked with the command 'fix'. the data editor changes the size of large data frames. a simple example illustrates this: ------------------------------------------------------- > dfrm <- data.frame(no=c(1:100000)) > length(dfrm[,1]) [1] 100000 > fix(dfrm) >

For the query below I have also included the follwing information. Thanks for your replies > str(FeaturePresenceMatrix) chr [1:65530, 1:40] "0" "0" "0" "0" "1" "0" "0" "0" "0" ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:65530] "4" "5" "6" "7" ...

Dear All, It's Eszter again from Hungary. I could not solve my problem form yesterday, so I still have to ask your help. I have a binary dataset of vegetation samples and species as a comma separated file. I would like to calculate the Jaccard distance of the dataset. I have the following error message: Error in rowSums(x, prod(dn), p, na.rm) : 'x' must be numeric In addition:

I am trying to construct a data set with some sequences for example: a = seq(0,1,0.1) m = matrix(nrow = 1331, ncol = 3) m[,1] = rep(a,121) m[,2] = rep(a,11,each = 11) m[,3] = rep(a,1,each = 121) I realize that there may be better ways of doing this, but this approach demonstrates the problem I'm having. I then want to get the sum of the rows and delete any row with a sum of greater than 1.

On Fri, 09 May 2003 11:34:08 +0300, Bernd Ebersberger <bernd.ebersberger@vtt.fi> wrote: >dear R-tists, > >i am experiencing a problem with the data editor in the windows version of >R 1.6.1 envoked with the command 'fix'. > >the data editor changes the size of large data frames. I can confirm this in the current R-patched. I'll take a look. It might be that

Dear R-brains, I'm rather new to state-space models and would benefit from the extra confidence in using the excellent package sspir. In a one-factor model, If I am trying to do a simple regression where I assume the intercept is constant and the 'Beta' is changing, how do I do that? How do i Initialize the filter (i.e. what is appropriate to set m0, and C0 for the example below)?

That's very helpful and instructive, thank you! Jason Stout, MD, MHS Box 102359-DUMC Durham, NC 27710 FAX 919-681-7494 ________________________________ From: John Fox <jfox at mcmaster.ca> Sent: Saturday, October 14, 2023 10:13 AM To: Jason Stout, M.D. <jason.stout at duke.edu> Cc: r-help at r-project.org <r-help at r-project.org> Subject: Re: [R] Create new data frame with