similar to: Time series (ts) questions.

Hi R community! I'd like to create a temporal series with ts command for the interval 1st January 2002 - 31 December 2008. I have daily values, so this is a 2557 days temporal series. I'm using this command : ts(observations, start=2002, end=2009, freq=365) However, I don't get the correct temporal series since both frequency (365 OR 366 for leap years) and deltat (1/365 OR

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"))

I have two time series a <- ts(1:10, start=c(1,6), end=c(2,5), frequency=10) b <- ts(1:5, start=c(2,1), end=c(2,5), frequency=10) Obviously 'b' is a subset of 'a'. I want a single index value indicating where that start of 'b' lines up with the start of 'a'. So in this simple example I would expect an index of 5. I was playing with 'merge'.

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

In a time series ts object, like the z1.ts below: z1 = array(1:235) z1.ts = ts(z1, frequency =12) I would like to select only a certain month, for instance the "February" data If I transform the data to a matrix, I have the problem that 235 is not a multiple of 12 I do not like to cut or add data, or program a loop to pick out the correct data. I am wondering if exist an easier

I have a need to build a time series and there are a couple of aspects about the time series object that are confusing me. First it seems that ts.union is not doing what I would expect. For example: x0 <- rep(0,10) x1 <- rep(1,10) xt0 <- ts(x0, frequency=10) xt1 <- ts(x1, frequency=10) st2 <- ts.union(xt0, xt1) > xt2 Time Series: Start = c(1, 1) End = c(1, 10) Frequency = 10

Can someone enlighten me on why the following doesn't work? setwd('C:/Temp/R') d <- rep(1:53,2) (s <- ts(d, frequency=53, start=c(2000,10))) n <- length(s) k <- n%/%3 for(i in (n-k):n) { st <- c(start(s)[1] + (start(s)[2] + i)%/%frequency(s), (start(s)[2] + i) %% frequency(s)) ed <- c(start(s)[1] +

I use R 2.7.0 on GNU/Linux. I have noticed a problem in cbind method for multivariate time series (ts) objects. Consider the following example: > t <- ts(data.frame(a = 10:20, b = 20:30, c = 30:40, d = 40:50)) > t1 <- t[, c('a', 'b')] > t2 <- t[, c('c', 'd')] > > colnames(t1) [1] "a" "b" > colnames(t2) [1]

I am running R 2.9.2 and creating a PDF that I am trying to open with Adobe Reader 9.2 but when I try to open it the reader responds with "There was an error opening this document. The file is damaged and cannot be repaired.: I am using the R command(s): pdf(file="cat.pdf", title="Historical Sales By Category") for(j in 1:length(master)) { d <-

Hi All, I have a very simple question about a time series object: how to access values for a particular year and quarter (say)? Suppose, following http://www.stat.pitt.edu/stoffer/tsa2/R_time_series_quick_fix.htm I have read in data as a time series; here is how it looks. * Qtr1 Qtr2 Qtr3 Qtr4 1960 0.71 0.63 0.85 0.44 1961 0.61 0.69 0.92 0.55 . . . . .

I'm stuck, but am sure it can be done I just don't understand how. I have data in an irregular timeseries. I want to be able to use stl to visualise the data (see seasonal parts etc), so I need to change to regular series of class ts (I think). I am using 2 zoo objects one is regular and the other is my irregular data. I am then merging to create the object I want but when I try to change

Hi, I am trying to convert a dataset (dataframe) into time series object using ts function in stats package. My dataset is as follows: >df [1] 11.08 7.08 7.08 6.08 6.08 6.08 23.08 32.08 8.08 11.08 6.08 13.08 13.83 16.83 19.83 8.83 20.83 17.83 [19] 9.83 20.83 10.83 12.83 15.83 11.83 I converted this into time series object as follows >tsdata <-

I don't understand the output of stl. As a simple example: y <- numeric(1:365) y[250] = 1 stl <- stl(ts(y, frequency=7), s.window="periodic") This returns without error but the results are puzzling to me. If you plot the results it is probably easiest to visualize what I mean. plot(stl) This shows the original data (a single spike at 250). A trend (which also shows a bump

Dear all, I have an error message, when I try to convert a zoo object (called test) to ts (on R 2.4.0, Package zoo version 1.2-1, Windows XP) > test 1994-05-10 1994-06-09 1994-07-09 0.0024943889 0.0024881824 0.0006955831 > str(test) atomic [1:3] 0.002494 0.002488 0.000696 - attr(*, "index")=Class 'Date' num [1:3] 8895 8925 8955 > is.regular(test) [1] TRUE

Hi everyone. I have have a dataset with daily measurement from January 1st of 1966 up to December 31th of 2011. Here's the first part of the data: Date SLEV 1/1/1966 1.086 1/2/1966 1.079 1/3/1966 1.133 1/4/1966 1.261 1/5/1966 1.391 1/6/1966 1.571 1/7/1966 1.728 1/8/1966 1.823 1/9/1966 1.97 1/10/1966 1.804 1/11/1966 2.02 1/12/1966 2.017 1/13/1966 1.86 1/14/1966 1.96 1/15/1966 1.813 1/16/1966

Full_Name: Yan Wong Version: 2.8.0 OS: Mac OS X 10.4 Submission from: (NULL) (78.149.183.231) When plotting multiple time series in a single plot, via plot.ts(plot.type="multiple"), the cex.lab, col.lab, and font.lab arguments are ignored > plot(ts(data.frame(a=1:10, b=1:10)), plot.type="single", cex.lab=0.5, col.lab="red") #tiny red axis labels >

Paul wrote to R-devel : PaulG> ts() is giving me problems on Solaris: PaulG> R : Copyright 1999, The R Development Core Team PaulG> Version 0.64.0 (April 8, 1999) PaulG> ... >> z <- ts(matrix(1:20,10,2), start=c(1969,1), frequency=12) >> max(abs(z-z)) PaulG> Error: invalid time series parameters specified >> traceback()

I have a bunch of lists that are essentially time-series with the unit of time being 'day'. So I naturally want to generate a time-series from 1:365. I was wondering if there is a nifty 'R' trick to turn a list with missing data (the list may contain values at 100, 230, and 360) into a time series with the missing data filled in (with zeros). Thank you. Kevin

Hello, I am trying to conduct a time series analysis on historic hydrologic data, but I cannot coerce it into class ts because it does not have regular sampling intervals (some years have 20 samples, other have 8). Specifically I am trying to perform a CUSUM or or other step change detection, but the packages all seem to require data as ts. Is there a way to coerce my data into ts while

Howdy! I am attempting to convert a date frame with irregular dates into a regular time series, aggregated by date. i have tried using both the 'its' and 'zoo' packages. I have something like times<-c("2003-03-05", "2003-03-05", "2003-05-05" ,"2003-04-07" ,"2003-03-05") aarf<-data.frame(times) aarf$x<-runif(5) what i