similar to: rollapply() by time, not entries (width)

Here is a relatively simple script (with comments as to the logic interspersed): # Some of these libraries are probably not needed here, but leaving them in place harms nothing: library(tseries) library(xts) library(quantmod) library(fGarch) library(fTrading) library(ggplot2) # Set the working directory, where the data file is located, and read the raw data

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

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 =

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()

Hi. I'm comparing output from rollapply.zoo, as produced by two versions of R and package zoo. I'm illustrating with an example from a R-help posting 'Zoo - bug ???' dated 2010-07-13. My question is not about the first version, or the questions raised in that posting, because the behaviour is as documented. I'm puzzled as to why na.rm no longer is passed to mean, i.e. why

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

# Hi there, # I am trying to apply a function over a moving-window for a large number of multivariate time-series that are grouped in a nested set of factors. I have spent a few days searching for solutions with no luck, so any suggestions are much appreciated. # The data I have are for the abundance dynamics of multiple species observed in multiple fixed plots at multiple sites. (I total I

Hi, I faced with problem when start using function - rollapply(returns, 3 , mean) Error in UseMethod("rollapply") : No suitable Method for "rollaply" How can I fix the problem? Thank you for help. -- Best regards, Andy Fetsun [[alternative HTML version deleted]]

#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,

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

Hi all, I wonder if there is any way to calculate a moving average on an irregular time series, or use the rollapply function in zoo? I have a set of dates where I want to check if there has been an event 14 days prior to each time point in order to mark these timepoints for removal, and can't figure out a good way to do it. Many thanks in advance! Gustaf Example data:

Dear R users. I have zoo object "size_june" containing market-capital values: > dim(size_june) # market-cap data of 625 firms for 20 years [1] 20 625 > class(size_june) [1] "zoo" > size_june # colnames = "size.firmcode" size.34020 size.4710 size.11050 size.10660 size.9540 size.8060 size.16160 size.8080 size.9280 1988-06-30 NA

Hello I have a vector a =(-2,0,0,0,1,0,0,3,0,0,-4) I want to replace all zeros into previous non-zero state. So for instance the above vector should be converted into: a= (-2,-2,-2,-2,1,1,1,3,3,3,-4) I tried many things and finally concluded that probably(?) rollapply may be the best way? I tried f= function(x){ ifelse(x==0,Lag(x),x) } And then, rollappy(a,1,f) and that

Dear List members I want to do the sliding window analysis of some specific values. Here is my code: require(zoo) dat <- read.table("chr1.txt", header = TRUE, sep="\t") dat2 <- cbind(dat[1,3]) #The first column is also important. It represents the position of the site on the chromosome. TS <- zoo(c(dat2)) a <- rollapply(TS, width=1000000, by=200000, FUN=mean,

# 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)

Dear useRs, the new version 1.2-0 of the zoo package for dealing with regular and irregular time series data is available from the CRAN mirrors. This version includes two important changes/enhancements: - rapply() was re-named to rollapply() because from R 2.4.0 on, base R provides a function rapply() for recursive (not rolling) application of functions, which was already described in

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)]

Hello: I want to get a rolling estimation of the stdev of my data. Searching the document, I found the function "rollapply" in the zoo package. For example, my series is "c", and i want get a period of 10 days, so i write the command below: roll.sd = rollapply( c, 10, sd, na.pad = TRUE, align = 'right' ) but there is an error in it ,and the computing cannot be

Hi everyone, I'm experiencing difficulty getting the results I want when I use a nested for loop. I have a data set to which I perform some calculations, and then try to apply a regression over a rolling window. The code runs, but the regression results I am getting (intercept and slope) are simply the same, repeated again and again in the results matrix. The regression does not seem to be