similar to: Yearly aggregates and matrices

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

Hi list, I would like to use the following data.frame to generate matrices over a 3 year moving window: DF = data.frame(read.table(textConnection(" A B C 80 8025 1995 80 8026 1995 80 8029 1995 81 8026 1996 82 8025 1997 82 8026 1997 83 8025 1997 83 8027 1997 84 8026 1999 84 8027 1999 85 8028 1995 85 8029 1998"),head=TRUE,stringsAsFactors=FALSE)) Function to be

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 ~

# 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. 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

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

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 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

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

#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, 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 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

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

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 <-

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?

Hi, I'd like to make a time series at an annual frequency. > a<-xts(x=c(2,4,5), order.by=c("1991","1992","1993")) Error in xts(x = c(2, 4, 5), order.by = c("1991", "1992", "1993")) : order.by requires an appropriate time-based object > a<-xts(x=c(2,4,5), order.by=1991:1993) Error in xts(x = c(2, 4, 5), order.by =

Hi All, I was looking for a function to find a small matrix inside a larger matrix in R similar to the one described in the following link: https://www.mathworks.com/matlabcentral/answers/194708-index-a-small-matrix-in-a-larger-matrix I couldn't find anything. The above function can be seen as a "generalisation" of the "which" function as well as the function described

Dear all, I am having a vector of around 300.000 elements and I Want to slide fast a window from the first element until the last-Windowsize what I have so far is the following for statement:  for (i in 1:(length(data[,1]) - windowSize)) {         out[i] <- mean(data[i:(i + windowSize - 1), ])         elements[i]<-length(i:(i + windowSize - 1))       } but this of course takes ages to

Hello, I am writing codes for time series computation but encountering some problems Given the quarterly data from 1983Q1 to 1984Q2 PI1<-ts(c(2.747365190,2.791594762, -0.009953715, -0.015059485, -1.190061246, -0.553031799, 0.686874720, 0.953911035), start=c(1983,1), frequency=4) > PI1 Qtr1 Qtr2 Qtr3 Qtr4 1983 2.747365190 2.791594762