similar to: daily time series in R

Hi All, I have a data set of daily measurements of river flow. I would like to create a "ts" object from this data. Here's a sample data set: date <- as.Date(c(1:300), format="%Y") year=as.numeric(format(date, format = "%Y")) month=as.numeric(format(date, format = "%m")) julianday=as.numeric(format(date, format = "%j"))

A new version of tseries (0.9-10) has been uploaded to CRAN. The new version contains the class "irts" for irregularly spaced time series. Irregular time series are basically time series where each observation (uni- or multivariate) has a time-stamp represented by an object of class "POSIXct". It provides some basic functionality such as reading and writing irregular time

A new version of tseries (0.9-10) has been uploaded to CRAN. The new version contains the class "irts" for irregularly spaced time series. Irregular time series are basically time series where each observation (uni- or multivariate) has a time-stamp represented by an object of class "POSIXct". It provides some basic functionality such as reading and writing irregular time

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

Hi R-users: How can I format a daily time serie with ts function so the plot of the time shows the date right (dd/mm/yy) or yy.xxxx ? Excerp of the database: FECHA TRM 1 01/01/2000 1873.77 2 02/01/2000 1873.77 3 03/01/2000 1873.77 4 04/01/2000 1874.35 5 05/01/2000 1895.97 . . . 1397 10/11/2003 2843.82 1398 11/11/2003 2840.41 1399 12/11/2003 2840.41 1400 13/11/2003

Hi R-list, I'm working with irregular time series (time series of climate data, daily data 365/6 days a year) and would like to create regular time series from them ( irts e.g. Rain <- irts(as.POSIXct(Climate[,1]),Climate[,5]) to ts e.g. test <- ts(x, start=c(1997,1), frequency=365) ) such that I can find where the gaps (lacking temperature data, ...) are and try

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

Is there an elegant way to do operations (+/-/*/ / ) on zoo/xts objects when one serie is monthly (end of month) and the other daily (weekdays only) - typically a monthly economic indicator and a stock index price? Thanks, TDB -- View this message in context: http://r.789695.n4.nabble.com/How-to-do-operations-on-zoo-xts-objects-with-Monthly-and-Daily-periodicities-tp3558081p3558081.html

Hi I have data that is sampled (in time) with a certain frequency and I would like to express this time series as a time series of a higher (or lower) frequency with the newly added time points being filled in with NA, 0, or perhaps interpolated. My data might be regularly or irregularly spaced. For example, I might have quarterly data that I would like to handle as a monthly time series with

Having to collect hourly electricity loads and quarter-of-an-hour electricity production data for some years I think that the tidiest way of doing it is to resort to ts but I don't know how to define such a frequency starting from a set date. Leafing through r-help mail archives I've found this *ALMOST* satisfactory message: ==========================================================

I have three time series, x, y, and z, and I want to analyse the relations between them. However, they have vastly different resolutions. I am writing to ask for advice on how to handle this situation in R. x is a stimulus, and y and z are responses. x is a rectangular pulse 4 sec long. Its onset and offset are known with sub-millisecond precision. The onset varies irregularly -- it doesn't

Hi, all Here I created a data frame like mydates<- seq(as.Date("2010-05-29"), length = 43, by = "day") myvalues<-runif(43,0,1) myframe<-data.frame(dates=mydates, day=weekdays(dates), value=myvalues) dates day value 1 2010-05-29 Saturday 0.14576143 2 2010-05-30 Sunday 0.37669604 3 2010-05-31 Monday 0.74813943 4 2010-06-01 Tuesday

(Sorry for reposting. Please delete previous msgs. Thanks!) Hi, all Here I created a data frame like mydates<- seq(as.Date("2010-05-29"), length = 43, by = "day") myvalues<-runif(43,0,1) myframe<-data.frame(dates=mydates, day=weekdays(dates), value=myvalues) dates day value 1 2010-05-29 Saturday 0.14576143 2 2010-05-30 Sunday 0.37669604

R users, I am trying to generate a randomized weekday survey schedule that ensures even coverage of weekdays in the sample, where the distribution of variable DOW is random with respect to WEEK. To accomplish this I need to randomly sample without replacement two weekdays per week for each of 27 weeks (only 5 are shown). However, I need to sample from a sequence (3:7) that needs to be

I am new to R and am trying to solve the following problem: I have a data file containing tick-by-tick, millisecond level prices for some stocks. I have another file or two containing orders and trades, again, with millisecond time-stamps. Both of these files are irregularly spaced and the time stamps are in an iso format (<date> <time>.<millisecond>) I would like to create a

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

Hi, Is it possible to create a ts() object, whose data is daily based BUT measured only on working days? In other words, suppose I have a data set with 255 observations, measured from 29 June 1959 to 30 June 1960. How would I create such a data? I tried something like: ts(c(...), start(1959, 180)) but I'm not sure what to use for frequency. In other words I don't know how to

Hello I have daily S&P 500 from 1950 for which I would like to do some time series analysis in R. Could someone please show me an example of how to create a ts/ irts object for my data? Additionally, how do I create monthly subsamples of the data. I've experimented with the window function but haven't had any luck. Thank you Ian Confidential: This electronic message and

Good day: I am trying to use readcsvIts("nwr_data_qc.txt",informat=its.format("%Y%m%d%h%M %Y"),header=TRUE,sep="",skip=0,row.names=NULL,as.is=TRUE,dec=".") to read in a file (nwr_data_qc.txt) that looks like this: Time Y M D H Min CO2 2000.18790 2000. 3. 9. 18. 30. 373.60 2000.20156 2000. 3. 14. 18. 30. 373.34

Hi, I have a bunch of irregularly spaced xts time series (with a POSIX index), and I'm trying to write a function that fillls the missing days. Using a solution suggested by Gabor Grothendieck for zoo, I wrote the following: # FD: Fill missing days FD<-function(ser) {rng<-range(time(ser)) > temp<-merge(ser,xts(,seq(rng[1],rng[2],"day"))) >