similar to: (newbie) sum for certain number of rows

#using "rollapply" to calculate a moving sum or running sum? #I am tryign to use rollapply to calcualte a moving sum? #I tried rollapply and get the error message #"Error in seq.default(start.at, NROW(data), by = by) : # wrong sign in 'by' argument" #example: mymatrix <- ( matrix(data=1:100, nrow=5, ncol=20) ) mymatrix_cumsum <- ( matrix(data=NA, nrow=5,

Hello! My setup is Rails 1.1 with Apache 2.x proxying the Rails stuff to lighttpd. I know how to set up Apache to secure my entire Rails app to require a username/password challenge. Is it possible to set up the challenge for only parts of my application? E.g., let''s say I have a "pub" controller whose views are accessible to anyone. I am already implementing user

Hello, I'm new to R and would like to know how to create a vector of "rolling sums". (I have seen the Rmetrics package and the rollMean function and I would like to do the same thing except Sum instead of Mean.) I imagine someone has done this, I just can't find it anywhere. Example: x <- somevector #where x is 'n' entries long #what I would like to do is: x1

I have a huge matrix and need to delete certain rows. What I need to do is: 1.In each row, calculate the sum of jth column and (J+2)th column 2. If the sum is greater than 2 then that row needs to be deleted. I have a sample matrix and my codes here. It does remove some rows but when it does, it skips the next row and each time it deletes a row, the dimension changes so it gets out of bound. I

Dear friends, If I have a table like this, first row A B C D ... are different levels of the variable, first column 0 1 2 4 ... are the levels of the "numbers", the numbers inside the table are the probabilities of the "number" occuring. A B C D ... 0 0.2 0.3 0.1 0.05 1 0.1 0.1 0.2 0.2 2 0.02 0.2 0 0.1 4 0.3 0.01 0.01

zoo's rollapply() function appears to be extremely useful for plugging in a function on-the-fly to run over a window. With inline, there is a lot more coding and room for error, and the code is less portable because the user has to have R compiling set up or it won't work. However, rollapply() seems to be really slow. Several orders of magnitude slower than inline, in fact. I don't

Dear friends, I have a table like this, I have A B C D ... levels, the first column you see is just the index, and there are different numbers in the table. A B C D ... 1 0 2 1 0 2 1 0 2 1 3 2 3 0 0 4 0 0 1 0 5 0 2 3 1 ... I want to calculate the frequencies or the percentages of the numbers in every column. How do I get a table like this,

Hi, Sorry ahead of time for not including data with this question. Using rollapply to calculate mean values for 5 day blocks, I'd use this: Roll5mean <- rollapply(data, 5, mean, by=5, align = c("left")) My question is, can someone tell me how to fill in the days between each of these means with the previously calculated mean? If this doesn't make sense, I will clarify and

- This avoids problematic "reloc'ed while mapped" messages and some associated corruption as well. Signed-off-by: Maarten Maathuis <madman2003 at gmail.com> --- src/gallium/drivers/nouveau/nouveau_screen.c | 21 +++++++++++++++++++++ src/gallium/drivers/nouveau/nouveau_screen.h | 3 +++ src/gallium/drivers/nouveau/nouveau_stateobj.h | 13 +++++++++++++

Hello everyone, I have a dataframe with 1 column and I'd like to replace that column with a moving average. Example: > library('zoo') > mydat <- seq_len(10) > mydat [1] 1 2 3 4 5 6 7 8 9 10 > df <- data.frame("V1" = mydat) > df V1 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 > df[df$V1 <- rollapply(df$V1, 3, mean)]

Hi I would like to understand how to extend the function (FUN) I am using in rollapply below. ###################################### With the following simplified data, test1 yields parameters for a rolling regression data = data.frame(Xvar=c(70.67,70.54,69.87,69.51,70.69,72.66,72.65,73.36), Yvar =c(78.01,77.07,77.35,76.72,77.49,78.70,77.78,79.58)) data.z = zoo(d) test1 =

# need zoo to use rollapply() # your data (I called df) df <- structure(list(a = 1:2, b = 2:3, c = c(5L, 9L), d = c(9L, 6L), e = c(1L, 5L), f = c(4, 7)), .Names = c("a", "b", "c", "d", "e", "f"), class = "data.frame", row.names = c(NA, -2L)) # transpose and make a zoo object df2 <- zoo(t(df)) #rollapply to get

Hi folks, I am confused whether the following is a bug or it is fine Here is the explanation a <- zoo(c(NA,1:9),1:10) Now If I do rollapply(a,FUN=mean,width=3,align="right") I get > rollapply(a,FUN=mean,width=3,align="right") 3 4 5 6 7 8 9 10 NA NA NA NA NA NA NA NA But I shouldn't be getting NA right ? i.e for index 10 I should get (1/3)*(9+8+7)

Hi everyone, I have a rollapply statement that applies a function, in steps, over a data matrix as follows: #Code start testm<-rollapply(mat, 100, by=100, min, na.rm=F) #Code end This moves down matrix 'mat' and calculates the minimum value over a 100 row range, every 100 rows (i.e. no overlaps). NAs are not removed. I want to modify this statement somehow so that the rollapply()

Dear Colleagues, I have faced with the problem that function rollaply with rolling window for calculation of volatility doesn't give the all results of calculations. I have run the rolling window for calculation in Excel and obtained that the number of outputs for Excel is 36 and for R is 18. The total number of observations is 37. In the attachment you can find pdf of the Excel and Excel

I found this from ocfs1.4 document: g) NFS OCFS2 volumes can be exported as NFS volumes. This support is limited to NFS version 3, which translates to Linux kernel version 2.4 or later. Users must mount the NFS volumes on the clients using the nordirplus mount option. This disables the READDIRPLUS RPC call to workaround a bug in NFSD, detailed in the following link:

Hi, I need to perform calculations on subsets of a data frame: DF = data.frame(read.table(textConnection(" A B C D E F 1 a 1995 0 4 1 2 a 1997 1 1 3 3 b 1995 3 7 0 4 b 1996 1 2 3 5 b 1997 1 2 3 6 b 1998 6 0 0 7 b 1999 3 7 0 8 c 1997 1 2 3 9 c 1998 1 2 3 10 c 1999 6 0 0 11 d 1999 3 7 0 12 e 1995 1 2 3 13 e 1998 1 2 3 14 e 1999 6

Thanks Dragos, I assume I will be setting those parameters during initialization of encoder right? Question is, if connection gets too lossy, how will opus adapt to it? Can it automatically shift bitrate down to minimize impact? Mark from IRC suggests that the app has to be aware of the losses and change it on the fly. Has anybody on the list tried this? Kelvin Chua On Wed, Mar 4, 2015 at 5:53

hi all members, please, i need you help... now a i´m working with veronoi polygons in a area with projections, but i need cut the polygons left. On other words, i need cut the polygons in the worked area. R help say that use the command voronoi.findrejectsites, but in this command i need put the numbers, any way...this command not cut!! do you can help me? Thank you for help me! José Bustos

Dear R-users, I am working on a problem that I am currently not able to solve efficiently. It is about multiplying one column of a matrix with only a certain number of rows of another matrix. Let me illustrate my problem with an example: n.obs = 800 n.rowsperobs = 300 n.param = 23 Designmat = matrix(rnorm(n.obs*n.rowsperobs*n.param),ncol=n.param) Betamat =