similar to: Aggregating frequency of irregular time series

Dear all, I would like to aggregate a data frame (consisting of 2 columns - one for the bins, say factors, and one for the values) along bins and quantiles within the bins. I have tried aggregate(data.frame$values, list(bin = data.frame $bin,Quantile=cut2(data.frame$bin,g=10)),sum) but then the quantiles apply to the population as a whole and not the individual bins. Upon this

Dear all, S+Finmetrics has a number of very specilised functions. I am particularly interested in the estimation of cointegrated VARs (chapter 12 of Zivot and Wang). In this context the functions coint() and VECM() stand out. I looked at package "dse1", but found no comparable functionality. Are there any other packages you could point me to? In general, are there efforts for

Folks, I have the following repetitive code which works correctly: A = read.table(file="junior.csv", sep=",", col.names=c("date", "l")); A$date = chron(as.character(A$date), format="m/d/y"); r.junior = levels2weeklyret(lastfriday, A$date, A$l); plot(A$date, A$l, type="l", col="red", main="Junior levels")

Hi all I have some tick-by-tick data and I have calculated the intraday returns. I want to sum up the intraday squared returns to calculate the daily volatility(or daily variance). I know that the s-plus FinMerics has the function aggregateSeries function that can be apply to daily data: aggregateSeries(x, Fun, by="daily"), but the counterpart function in R:applySeries can not be apply

Hello R users, I'm a newby to R (and programming software at large) and I would need some help to sum up event data at discreet time and irregular time interval into a hourly frequency. Here is an example of my time series frame (irregular time-serie object - irts in the tseries package): time value 2008-12-19 19:11:03 GMT 1 2008-12-19 19:12:00 GMT 0 2008-12-19

I have a monthly price index series x, the related return series y = diff(log(x)) and a POSIXlt date-time variable dp. I would like to apply annual blocks to compute for example annual block maxima and mean of y. When studying the POSIX classes, in the first stage of the learning curve, I computed the maximum drawdown of x: > mdd <- maxdrawdown(x) > max.dd <- mdd$maxdrawdown > from

I make quite a lot of use of irregular time-series, and had already spent a bit of time writing an 'its' class when the 'irts' class was released via the package 'tseries'. I have experimented with the 'irts' class, and have some practical issues with its use. In some applications of irregular time-series (in my case these are financial and econometric) there are

Hi, I realized that when I have irregular series to feed into lineChart, the interval of each point in the chart does not seem to take care of irregular time interval I specified in my input xts time series. But rather, lineChart seems to take each point as equal spaced time series. For example, I have the following code: library(quantmod) options(digits.sec=3) t0 <-

Dear R developpers, I am a user of Splus since many years and I have developped lots of functions to plot graph of data and model results of irregular or regular times series. In Splus regular times series are created using the rts function and irregular time series using the its functions. In both cases, times is given as a numeric vector. There is no problem in plotting a regular and an

What package is aggregateSeries in? It is referred to in the fCalendar document but I do not see it in the package.

Could smb please help with try-catch encapsulating a function for downloading. Let's say I have a character vector of symbols and want to download each one and surround by try and catch to be safe # get.hist.quote() is in library(tseries), but the question does not depend on it, I could be sourcing local files instead ans=null;error=null; for ( sym in sym.vec){

I know this: > library(date) > x="1979-04-04" > try=as.date(x, "ymd") > print(try) [1] 4Apr79 and that `x' here has to be a string, e.g.: > x=1979-04-04 > print(x) [1] 1971 I'm stuck in reading from a file. I say: > A <- read.table(file="try") > print(A) V1 V2 1 1979-04-04

Hi, I would like to import some daily financial data from excel via csv. More specifically, I would like to be able to use the ts.union function from the tseries library as the dates are irregular and I need to line up the dates so that I can place all the variables into one data frame. The trouble is, how do I import the dates from excel into R? At the moment I'm just importing the data

R: Is there an easy way to get the acf and pacf for an irregular times series? That is, the acf and pacf with lag lengths that are in units of time, not observation number. Thanks, Jason Higbee Research Associate Federal Reserve Bank of St. Louis The views expressed in this email are the author's and not necessarily those of the Federal Reserve Bank of St. Louis or the Federal Reserve

Dear all, I obtained and successfully compiled R 2.1.0 on Mac OSX 10.3.9. The flags used for configuration are: ./configure --enable-utf8 --enable-R-shlib --with-blas='-framework vecLib' --with-lapack --with-aqua --with-tcl-config=/Library/Frameworks/Tcl.framework/tclConfig.sh --with-tk-config=/Library/Frameworks/Tk.framework/tkConfig.sh TCLTK_LIBS='-framework Tcl -framework

Hi, I have a couple of aggregation operations that I don't know how to accomplish. Let me give an example. I have the following irregular time series time x 10:00:00.021 20 10:00:00.224 20 10:00:01.002 19 10:00:02:948 20 1) For each entry time, I'd like to get sum of x for the next 2 seconds

Hello everybody, I've got a matrix called EUROPEDATA and I want to calculate the adf test statistic (part of the tseries package) on a rolling basis for window my.win on each column; i.e. each column of EUROPEDATA represents a particular variable; for the first column I calculate the adf test statistic for window my.win = 60 for example, roll forward one observation, calculate the adf

hi guys: sorry, one more. I have irregularly spaced time series, often with big gaps. a good analogy is: tsvec <- ts(c(1,NA,2,NA,1, NA, 2),freq=12, start=c(1965,12)) Unfortunately, plot( tsvec ) does not plot the data. is it possible to convince plot to just ignore the NA items (either with points or lines) help appreciated. /iaw

Hello, I am trying to switch to R from S-PLUS 6.1, and one problem I am having is using R for manipulation of calendar-based time-series. In S-PLUS, I commonly use the functions timeSequence(), timeDate(), and timeSeries() to align/average/aggregate data; and I also do a lot of plotting of time-series data (with calendar-based labels on the x-axis). I was wondering if anyone is familiar with

Hello all, I'm sorry if my question seems basic. Im studying a responses (Yes,No) in a survey and, thanks to GLM I obtain the following relation with my variables : (Yes,No)~ ?0 + Age We note this this certain type of (Yes,No) response is linked to age (p<0.05 in glm) . After that we calculated : model1=glm(cbind(Yes,No) ~ Age + Times + Type, family=binomial) summary(model1)