search for: rollappli

Displaying 20 results from an estimated 122 matches for "rollappli".

Did you mean: rollapply
2013 Jun 27
3
using "rollapply" to calculate a moving sum or running sum?
#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,
2009 Mar 23
1
performance: zoo's rollapply() vs inline
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
2010 Apr 09
3
"fill in" values between rollapply
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
2010 Jan 13
1
Rollapply
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 =
2008 Jul 31
1
rollapply() to portions of a matrix
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()
2011 Aug 12
2
rollapply.zoo() with na.rm=TRUE
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
2009 Jul 07
1
Error in Rolling window of function - 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
2009 Jun 19
1
function rollapply
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]]
2012 Oct 26
1
rollapply() by time, not entries (width)
Hi all- Thank you for reading my post. Please bear in mind that I'm very much a newbie with R! My question is this: I'm trying to use rollapply() on an irregular time series so I can't simply use the width parameter (I don't think). Rather than last 5 entries, I'd like to rollapply on last 6 months (for example). What would be the proper course of action for this? Thanks!
2011 Apr 03
1
zoo:rollapply by multiple grouping factors
# 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
2011 Dec 02
2
Moving column averaging
# 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
2012 Jul 08
3
How to replace a column in a data frame with another one with a different size
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)]
2010 Jul 13
2
Zoo - bug ???
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)
2012 Jan 24
1
problems with rollapply {zoo}
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
2011 Apr 09
5
Yearly aggregates and matrices
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
2007 Nov 30
1
rollapply on zoo object
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
2006 Oct 03
2
maybe use voronoi.findrejectsites?
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
2012 Jul 10
1
Help with vectors and rollapply
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
2010 Apr 02
1
All sub-summands of a vector
Hello, I'd like to take all possible sub-summands of a vector in the quickest and most efficient way possible. By "sub-summands" I mean for each sub-vector, take its sum. Which is to say: if I had the vector x<-1:4 I'd want the "sum" of x[1], x[2], etc. And then the sum of x[1:2], x[2:3], etc. And then...so on. The result would be: 1 2 3 4 2 5 7 6 9 10 I can
2012 Oct 16
2
sliding window analysis with rollapply
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,