similar to: Calculating variances in a moving window

Hello, I have a data frame containing time (e.g. GMT), and I would like to create/add a new variable that would be the computation of the elapsed time since the first observation. Does anyone have a suggestion for an easy way to do this? I am having trouble creating a new variable that would contain just the first time observation (then I could take difference between actual time and

Hi, I have a data.frame of the following type: F = data.frame(read.table(textConnection(" A B 1 1 4 2 1 3 3 1 1 4 1 4 5 1 2 6 1 2 7 1 2 8 2 1 9 2 1 10 2 1 11 2 1 12 3 2 13 3 4 14 3 1 15 3 1 16 3 1"),head=TRUE,stringsAsFactors=FALSE)) F A B 1 1 4 2 1 3 3 1 1 4 1 4 5 1 2 6 1 2 7 1 2 8 2 1 9 2 1 10 2 1 11 2 1 12 3 2 13 3 4 14 3 1 15 3 1 16 3 1

# 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

#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,

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

Hello, I would like to run a series of regressions on my data (response variable over time): 1) regression from T1 to T2 2) regressions from T1 through T3 3) regression from T1 through T4, etc. I have been struggling to find a way to do this through commands, as opposed to cutting up the data manually (my dataset has over 6000 rows/observations). An illustrative dataset can be created thusly:

Hi list, based on the following data.frame I would like to create a variable that indicates the number of occurrences of A in the 3 years prior to the current year: DF = data.frame(read.table(textConnection(" A B 8025 1995 8026 1995 8029 1995 8026 1996 8025 1997 8026 1997 8025 1997 8027 1997 8026 1999 8027 1999 8028 1995 8029 1998 8025 1997 8027 1997 8026 1999 8027 1999

Hello Lets say as an example I have a dataframe with the following attributes: rownum(1:405), colnum(1:287), year(2000:2009), daily(rownum x colnum x year) and foragePotential (0:1, by 0.01). The data is actually stored in a netcdf file and I'm trying to provide a conceptual version of the data. Ok. I need to calculate a moving mean and a moving variance for each cell on the following

Hope someone can help me here. I have a daily time series, say 2003-02-01 2003-02-03 2003-02-07 2003-02-09 2003-02-14 .......... 2004-02-01 2004-02-04 0.4914798 -1.1857653 -1.6982844 -0.3559572 -0.2333087 ........... 0.44553 -0.45222 I need to calculate the statistics for the overlapping rolling yearly window with rolling step as 1 day so for each of the intervals: (2003-02-01 ~

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 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

Hello there, I am trying to compute the 3 months return momentum with the timeSeries x.ts, which is just a subset of simple returns from a much bigger series, > class(x.ts) [1] "timeSeries" attr(,"package") [1] "timeSeries" > dim(x.ts) [1] 20 3 > x.ts[1:8,] GMT MS.US AAPL.US CA.FP 1996-01-31 0.15159065 -0.133391894

I'm having trouble returning a rolling n period highest value for a data set. For each day I want to calculate the highest value over the last 3 days. I am using the following packages: zoo, xts, quantmod and TTR. Thanks, Jason GLD.Close 2010-10-01 128.91 2010-10-04 128.46 2010-10-05 130.99 2010-10-06 131.81 2010-10-07 130.37 2010-10-08 131.66 2010-10-11

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

Good morning, I have discovered what I believe to be a performance regression between Zoo 1.6x and Zoo 1.7-6 in the application of rollapply. On zoo 1.6x, rollapply of my function over my data takes about 20 minutes. Using 1.7-6, the same code takes about 6 hours. R --version R version 2.13.1 (2011-07-08) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform:

Hello Imagine I have a vector with ones and zeroes I write it compactly: 1111111100001111111111110000000001111111111100101 I need to get a new vector replacing the "N" ones following the zeroes to new zeroes. For example for N = 3 1111111100001111111111110000000001111111111100101 becomes 1111111100000001111111110000000000001111111100000 I can do it with a for loop but I've read

Also note that the functionality discussed could be regarded as a generalization of matrix multiplication where * and + are general functions and in this case we have * replaced by == and + replaced by &. On Fri, Oct 11, 2019 at 10:46 AM Gabor Grothendieck <ggrothendieck at gmail.com> wrote: > > Using the example in the link here are two one-liners: > > A <-

Hello, I have some ideas for packages that I want to provide on R-CRAN. One package alreads is working, but I have some warnings in when compiling. Also I don't know if the libraries in use are only working on Unix/Linux. So I have some general questions: - If I'm not sure if the code would also work on windows (needing some ceratain libraries or tools), would it be better to

Hi, I'm trying to figure out common approach on calculating MA on a dataset that contains column "time". After digging around, I believe functions rollmean and rollaply should be used. However I don't quite understand the requirements for the underlying data. Should it be zoo object type? Formatted in a special way? As an example, I'm looking to get calculated

Dear all, I would like to use the apply or a similar function belonging to this family, but applying for each column (or row) but let say for each q columns. For example I would like to apply a function FUN for the first q columns of matrix X then for q+1:2*q and so on. If I do apply (X, 2, FUN) it applies for each column and not for every q columns. Is that possible with any similar function?