similar to: RowSums Question

i have time series of momentum signal. I want to get the date of each of the "-1" signal period. for example , the first period of -1 signal begins on 2005-9-21 and ends on 2005-9-28. 2nd period of -1 signal begins on 2005-09-30 and ends on 2005-10-28. Thx Cameron date Px 200MA Signals 2005-09-15 26.27 25.83865 1 2005-09-16 26.07 25.83275 1

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

Dear list-member, I am currently developing a package with S4 classes. The NAMESPACE and DESCRIPTION is printed below. Within this package I have set a method "residuals" for two classes. In version 2.8.1 these two are reported whereas in R-Devel (2009-01-28 r47766). What have I missed? What has changed and how can I rectify the issue? Your help and pointers are welcome. For 2.8.1:

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,

Hi all I have a data frame with duplicate columns and i want to remove duplicates by adding rows in each group of duplicates, but have lots of NA's. Data: dfrm <- data.frame(a = 1:4, b= 1:4, cc= 1:4, dd=1:10, ee=1:4) names(dfrm) <- c("a", "a", "b", "b", "b") dfrm[3,2:3]<-NA dfrm a a b b b 1 1 1 1 1 1 2 2 2 2 2 2 3

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

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,

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

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.

Dear list, I have some trouble generating a frequency table over a number of vectors. Creating these tables over simple numbers is no problem with table() > table(c(1,1,1,3,4,5)) 1 3 4 5 3 1 1 1 , but how can i for example turn: 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0 into 0 0 1 1 1 0 0 2 0 1 0 3 My second problem is, sorting rows and columns of a matrix by the rowSums/colSums. I did it

> with the entirely different rowSums, but it has been around > for a long time.) A lot longer than rowSums ... > Bill Dunlap > Spotfire, TIBCO Software --- This made me smile. The rowsums function was originally an internal part of the survival package, used for fast computation of certain sums when there is a cluster() statement. It was Statistical

Dear R-List, I am sure there must be a very simple way to do this - I just do not know how... This is what I want to do: #my dataframe df<-data.frame(id=c("x01","x02","x03","x04","x05","x06"),a=c(1,2,NA,4,5,6),b=c(2,4,6,8,10,NA),c=c(NA,3,9,12,NA,NA),sum=c(3,9,15,24,15,6))    id    a     b     c   sum 1 x01  1     2    NA   3 2

(a) In R 2.12.2 rowsum can overflow if given an integer input: > rowsum(c(2e9L, 2e9L), c("a", "a")) [,1] a -294967296 > 2^32 + .Last.value [,1] a 4e+09 Should it be changed to coerce its x argument to numeric (double precision) so it always returns a numeric output? (b) When rowsum is given an x containing both NaN and NA it appears to use the last