search for: cumsums

Hello, I am searching for a function to calculate "partial" cumsums. For example it should calculate the cumulative sums until a NA appears, and restart the cumsum calculation after the NA. this: x <- c(1, 2, 3, NA, 5, 6, 7, 8, 9, 10) should become this: 1 3 6 NA 5 11 18 26 35 45 any ideas? thank you and best regards, stefan

Hi, First post here. Grateful for any help you can give. I have data which looks like this: id time x 1 12:01 5 1 12:02 14 1 12:03 6 1 12:04 3 2 12:01 98 2 12:02 23 2 12:03 1 2 12:04 4 3 12:01 5 3 12:02 65 3 12:03 23 3 12:04 23 But I want to add a column which is the cumulative sum of X, but only by id. I've used cumsum before, but not

Apologies for the empty email earlier! I have species abundance data sampled at a weekly frequency or sometimes monthly depending on the year. The goal is to identify the dates in an annual cycle in which the cumulative abundance of a species reaches some threshold. Here's an example of the data for 1 species over an annual period: "mc_pheno" is the object created from this data:

Hello! Is it posible to apply /cumsum()/ along the 3rd dimension of 3D array? Something like matrlab function - /cumsum (*A*,dim)/ which returns the cumulative sum of the elements along the dimension of *A* specified by scalar dim. Thanks in advance ?eljka -- View this message in context: http://r.789695.n4.nabble.com/cumsum-in-3d-arrays-tp4110470p4110470.html Sent from the R help mailing

Hi I noticed a small inconsistency when using sum() vs cumsum() I have a char-based series > tryjpy$long [1] "0.0022" "-0.0002" "-0.0149" "-0.0023" "-0.0342" "-0.0245" "-0.0022" [8] "0.0003" "-0.0001" "-0.0004" "-0.0036" "-0.001" "-0.0011"

>>>>> Tomas Kalibera >>>>> on Tue, 25 Aug 2020 09:29:05 +0200 writes: > On 8/23/20 5:02 PM, Rory Winston wrote: >> Hi >> >> I noticed a small inconsistency when using sum() vs cumsum() >> >> I have a char-based series >> >> > tryjpy$long >> >> [1]

I've a matrix like this: 1985 1.38 1.27 1.84 2.10 0.59 3.47 1986 1.05 1.13 1.21 1.54 0.21 2.14 1987 1.33 1.21 1.77 1.44 0.27 2.85 1988 1.86 1.06 2.33 2.14 0.55 1.40 1989 2.10 0.65 2.74 2.43 1.19 1.45 1990 1.55 0.00 1.59 1.94 0.99 2.14 1991 0.92

...764081 0.1791877 0.2276013 NA I want cumulative sums for each row. Here's the code that works until it reaches an NA, then returns all subsequent values as NA. Adding na.rm=TRUE returns the error: Error in FUN(newX[, i], ...) : 2 arguments passed to 'cumsum' which requires 1 cumsums <- apply(proportion, 1, cumsum) Thank you, Tracy [[alternative HTML version deleted]]

I recently traced a bug of mine to the fact that cumsum(s)[length(s)] is not always exactly equal to sum(s). For example, x<-1/(12:14) sum(x) - cumsum(x)[3] => 2.8e-17 Floating-point addition is of course not exact, and in particular is not associative, so there are various possible reasons for this. Perhaps sum uses clever summing tricks to get more accurate results? In some

Dear R users, I am using R version 2.0.1 (2004/11/15) on an i386-pc-mingw32 platform. I encounter the following problem while using cumsum: > a <- rep(0.01, 100) > b <- cumsum(a) > sum(a) == 1 [1] TRUE > b[100] == 1 [1] FALSE Am I missing something? Should cumsum have such an outcome? Thanks in advance for any clarifications any of you can offer. Regards, Makram Talih --

I have a question about using cumsum on subsets of a data frame. Suppose I have a frame that looks something like this > tmp f x y 1 left 1 0 2 left 2 0 3 left 3 9 4 left 4 10 5 left 5 23 6 left 6 45 7 left 7 13 8 left 8 2 9 left 9 6 10 right 1 10 11 right 2 26 12 right 3 9 13 right 4 50 14 right 5 78 15 right 6 20 16 right 7 7 17 right 8 20 18 right 9 19

I'm trying to create an xyplot with a "groups" argument where the y-variable is the cumsum of the values stored in the input data frame. I almost have it, but I can't get it to automatically adjust the y-axis scale. How do I get the y-axis to automatically scale as it would have if the cumsum values had been stored in the data frame? Here is the code I have so far:

...rwise the cumulative sums add 0 and returns a number where a NA should be. Here's the code that works until it reaches an NA, then returns all subsequent values as NA. Adding na.rm=TRUE returns the error: Error in FUN(newX[, i], ...) : 2 arguments passed to 'cumsum' which requires 1 cumsums <- apply(proportion, 1, cumsum) Thank you for any suggestions, Tracy [[alternative HTML version deleted]]

Hello everybody, Data is myd <- data.frame(id1=rep(c("a","b","c"),each=3),id2=rep(1:3,3),val=rnorm(9)) I want to get a cumulative sum over each of id1. trying aggregate does not work myd$pcum <- aggregate(myd[,c("val")],list(orig=myd$id1),cumsum) Please suggest a solution. In real the dataframe is huge so looping with for and subsetting is not a

Hi, I need to keep a running count of events that have happened in my data.frame. I found a document called usingR that had an example of doing this for random coin flips and I tried to modify it. It seems to sort of work in the beginning, but then it stops and I don't understand why. I'm trying to duplicate essentially the Excel capability of =SUM($A$1:$A(Row number)) The example

I would like to create a page of two graphs (2 rows by 1 col) and then draw vertical lines (segments?) on both graphs from the minimum values to the corresponding maximum value. So I have tried # > y <- rnorm(3000) > par(mfrow=c(2,1)) > plot(y,type="l") > plot(cumsum(y),type="l") > segments(1000,min(cumsum(y)),1000,max(cumsum(y))) > par(mfg=c(1,1)) >

Hi, x <- c(rep(1800000003L, 10000000), -rep(1200000002L, 15000000)) This is correct: > sum(as.double(x)) [1] 0 This is not: > sum(x) [1] 4996000 Returning NA (with a warning) would also be acceptable for the latter. That would make it consistent with cumsum(x): > cumsum(x)[length(x)] [1] NA Warning message: Integer overflow in 'cumsum'; use

Hi, my problem belongs to the basic ones. I want to get cumulated sum over the matrix columns by one command (if such exists). Ordinary R's cumsum(x) when x is: [,1] [,2] [1,] 1 5 [2,] 2 6 [3,] 3 7 [4,] 4 8 yields: 1 3 6 10 15 21 28 36 I want: [,1] [,2] [1,] 1 5 [2,] 3 11 [3,] 6 18 [4,] 10 26 Is there any command to do so?? best,

Hello, I would like to build a Lorenz curve and calculate a Gini coefficient in order to find how much parasites does the top 20% most infected hosts support. Here is my data set: Number of parasites per host: parasites = c(0,1,2,3,4,5,6,7,8,9,10) Number of hosts associated with each number of parasites given above: hosts = c(18,20,28,19,16,10,3,1,0,0,0) To represent the Lorenz curve: I

Hi! I noticed that cumsum behaves different than the other cumulative functions wrt. NaN values: > values <- c(1,2,NaN,1) > for ( f in c(cumsum, cumprod, cummin, cummax)) print(f(values)) [1] 1 3 NA NA [1] 1 2 NaN NaN [1] 1 1 NaN NaN [1] 1 2 NaN NaN The reason is that cumsum (in cum.c:33) contains an explicit check for ISNAN. Is that intentional? IMHO, ISNA would be better