similar to: Up- or downsampling time series in R

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 =

I'm quite new to R. I have a time series of annual state population estimates from census.gov, and I'd like to get a time series of monthly estimates, by a nonlinear interpolation. How can I do this in R? Thanks! [[alternative HTML version deleted]]

Dear useRs and developeRs, In my diploma thesis I work with a daily time series of glacier runoff data. I did already aggregate them to monthly means etc. Now i want to use just the summer values (I am indecisive by now what that means, but let's make it easy and use months like June). Is there a way to extract the data off this zoo into another zoo with frequency=1 ? Do you have

I am was going to look at the as.yearmon function in the zoo package and write a as.day function to aggregate a time series of 96 observations per day into the mean for each day, but I don't know how to look at the code so that I can convert it into something I can use. On top of that I believe that it is probably an S3 method and I haven't quite gotten that far in my programming

I am trying to get monthly means for a daily data series using zoo(). I have found an odd problem, that seems to be caused by zoo()'s handling of leap years. Here's my R script with 2 methods (freq=365, 366) for aggregating the daily data to monthly series: library(zoo) J_link <- "http://www.ijis.iarc.uaf.edu/seaice/extent/plot.csv" JAXA_data <- read.table(J_link,

Given a long zoo matrix, the goal is to "sweep" out a statistic from the entire length of the sequences. longzoomatrix<-zoo(matrix(rnorm(720),ncol=6),as.yearmon(outer(1900,seq(0,length=120)/12,"+"))) cnames<-c(12345,23456,34567,45678,56789,67890) colnames(longzoomatrix)<-cnames longzoomatrix[1:24,] 12345 23456 34567 45678

Folks, If I have a series mm of, say, monthly observations, and a series dd of daily dates, what's a good way of expanding mm such that corresponding to each day in dd within the corresponding month in mm, the values of mm are repeated? So e.g., if I have mm: mm <- c(15, 10, 12, 13, 11) names(mm)<-c("Nov 2008", "Dec 2008", "Jan 2009", "Feb

Folks, I have some weekly dataseries that I convert to monthly xts (with yearmon indices), and obtain the two following extracts: > str(sig) An 'xts' object from Apr 1998 to Sep 1998 containing: Data: num [1:6, 1] 0.0083 0.2799 -0.2524 -0.0119 0.18 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr "e1" Indexed by objects of class: [yearmon] TZ:

On Fri, 7 Apr 2006 16:09:53 +0200 Brandt, T. (Tobias) wrote: > Hi > > Is there a reason why as.matrix.zoo doesn't set the rownames to the > index like as.data.frame.zoo does? Yes, oversight, I think ;-) Added to the devel-version of zoo. I'll try to get it out to CRAN in the next days. Z > Thanks > > Tobias > > > > library(zoo) > > x.Date

New user here. My goal is pull daily averages from a long dataset. I've been working with some code I got from this list from https://stat.ethz.ch/pipermail/r-help/2009-March/191302.html The code how I have been using it is as follows: library(zoo) library(chron) DB<-read.table("/Users/me/Desktop/R/data.csv", sep=",", header=TRUE, as.is =TRUE) z<-zoo(LTER6$temp,

I could use some advice regarding xyplot. I've got 2 time series. Both cover approximately the same period of time (ie, 1940 to 2009). But one series has annual data and the other has monthly data. One refers to university enrollment; the other to unemployment rates. Both are currently in the same data frame. I'd like to use the monthly times series as a light grayscale background for a

hi everyone! hope you can help me here. i am a new R user. what i am trying to do is to find the maximum annual discharge from a daily record. i have a data.frame which includes date and the discharge. somewhat like this.. 10/1/1989 2410 10/2/1989 2460 10/3/1989 2890 ... ... ... 12/31/2005 5730 i have been browsing through the archives and fount out about the aggregate

Dear R community, I have the following two zoo objects: MONTHLY CPI > plot(z) > par("usr") [1] 1977.76333 2011.15333 70.39856 227.03744 > z=zooreg(cpius$Value,as.yearmon("1979-11"),frequency=12) > str(z) ?zooreg? series from Nov 1979 to Oct 2010 Data: num [1:372] 76.2 77 77.8 78.5 79.5 80.3 81.1 82 82 82.6 ... Index: Class 'yearmon' num [1:372]

A quick question x <- as.yearmon(2000 + seq(0, 23)/12) x [1] "Jan 2000" "Feb 2000" "Mar 2000" "Apr 2000" "May 2000" "Jun 2000" "Jul 2000" "Aug 2000" "Sep 2000" "Oct 2000" "Nov 2000" "Dec 2000" "Jan 2001" [14] "Feb 2001" "Mar 2001" "Apr

Dear all, given a daily time series data, I am able to calculate monthly average, quarterly average like:   library(zoo) dat <- zooreg(rnorm(500), start=as.Date("2000-01-01"), frequency=1) mo.ave <- aggregate(dat, as.yearmon(index(dat)), "mean") head(dat) head(mo.ave) However is there any direct way like above to calculate the weekly average, bi-monthly average?   Thanks

I have a matrix of zoo series. each series is in a column. x <- as.yearmon(2000 + seq(0, 23)/12) # 24 months of data, lets make 20 sets of random data testData <- matrix(rnorm(480),ncol=20) # make a zoo object and columns will hold the 20 series TestZoo <- zoo(testData,order.by=x) # now run lm for just one series. m <- lm(TestZoo[,1]~time(TestZoo))$coeff[2] m time(TestZoo)

Hi, I have a zoo object with monthly frequency : library(zoo) dat <- zooreg(rnorm(50), as.yearmon("2000-01-01"), frequency=12) Now I want to make a zoo object with daily frequency from "dat" wherein value for a each day for a particular month will be value of "dat" at that particular month. Is there any easy way to do that? Thanks, -- View this message in

Hello, This is a standard example in which I read the time series data from a csv file and create a zoo object: x0 <- read.csv(file="CPI.csv", header=TRUE) time_0<-as.yearmon("1981-01")+(0:371)/12 x0zoo<-zoo(x0, time_0) The data look like this: TIME CPI CPI_food CPI_Clothes CPI_House CPI_Rent 198101 62.1 55.34 103.45 65.24 61.43 198102 63.16 56.95

I have the following daily exchange rate series (from january 1st 1996 to december 31st 2008) and I want to obtain them monthly series from it. I've read about the 'zoo' library but I'm not getting it how to do it. These are the data (left column day-month-year, right column the index) 31/12/1993 1,12509 03/01/1994 1,12509 04/01/1994 1,12558 05/01/1994 1,1258 06/01/1994 1,12596

Dear Gabor, Thanks for your reply. however: > tail(DJd) ^DJI.Close 2010-04-01 10927.07 2010-04-05 10973.55 2010-04-06 10969.99 2010-04-07 10897.52 2010-04-08 10927.07 *2010-04-09 10997.35* > tail(ag) 2009-11-30 10344.84 2009-12-31 10428.05 2010-01-31 10067.33 2010-02-28 10325.26 2010-03-31 10856.63 *2010-04-30 10997.35 * It seems the script "makes up"