similar to: Multivariate ts -- arithmetic bug [ for SOME time-series ] (PR#178)

I think this is another one of the same kind of bugs in ts: Version 0.64.1 (May 8, 1999) ... > z <- ts(matrix(1:20,10,2), start=c(1969,1), frequency=12) > (z > 5) | (z < 2) Error: invalid time series parameters specified > Paul -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read

On 11-Dec-97 maechler@stat.math.ethz.ch wrote: >>>>>> "PaulG" == Paul Gilbert <pgilbert@bank-banque-canada.ca> writes: > > PaulG> I have a class "tframe" with more specific classes indicating > PaulG> how time is being represented, such as > > >> class(tframe(data)) > PaulG> [1] "ts"

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]

Dear R People: Is there a library for Multivariate time series, please? For some reason, I'm thinking that Dr. Paul Gilbert may have one? R Version 1.6.2 (i've updated!) for Windows Thanks so much! Sincerely, Erin Hodgess University of Houston - Downtown mailto: hodgess at uhddx01.dt.uh.edu

Hello to everyone! I have a question for you..I need to predict multivariate time series, for example sales of 2 products related one to the other, having the 2 prices like inputs.. Is there in R a function to do it? I saw dse package but I didn't find what a I'm looking for.. Could anyone help me? Thank you very much Giusy -- View this message in context:

Hi all, I'm looking for R packages that estimate multivariate time-series models or vector-autoregression (VAR) time-series models. Thanks David -- =========================================================================== David Kaplan, Ph.D. Professor Department of Educational Psychology University of Wisconsin - Madison Educational Sciences, Room, 1061 1025 W. Johnson Street Madison,

Hello to everyone! I am working on my final year project about multivariate time series. There are three variables in the multivariate time series model. I have a few questions: 1. I used acf and pacf plot and find my variables are nonstationary. But in adf.test() and pp.test(), the data are stationary. why? 2.I use VAR to get a model. y is the matrix of data set and I have made a once

Hi all, I would like to know whether there is any function in R were i can find the cross-correlation of two or more multivariate (time series) data. I tried the function ccf() but it seems like to have two univariate datasets. Please let me know. sincerely, sandeep -- Sandeep Joseph PhD Post Doctoral Associate Center for Tropical & Emerging Global Diseases Paul D. Coverdell Center,

Hi! I know that there is function in fBasics package for univariate Jarque-Bera test and a funtion for univariate Ljung-Box test in stats package. But I am wondering if there is a function somewhere to do the tests for multivariate time series? Thanks, John [[alternative HTML version deleted]]

Dear all, I found the following behaviour with pacf() in the multivariate case, set.seed(10) x <- rnorm(1000,sd=10000) y <- rnorm(1000,sd=1) pacf(ts(cbind(x,y)),plot=FALSE,lag.max=10) Partial autocorrelations of series 'cbind(x, y)', by lag , , x x y 0.047 ( 1) 0.000 ( -1) 0.011 ( 2) 0.000 ( -2) 0.005 ( 3) 0.000 ( -3) 0.013 ( 4)

I have a multivariate time series and I would like to build a forecasting model with both AR and MA terms, I think that this is possible in R. I have looked at the vars package and it looks like it is possible to estimate MA terms using the Phi and Psi functions but I am not sure how to incorporate the estimated terms into a forecasting model. I have also looked at the dse package, but have not

Hi all, Can anyone here please tell me whether is it possible to produce a chart displayed in http://www.datawolf.blogspot.com/ in R for visualizing multivariate time series? If possible how? Regards, --------------------------------- [[alternative HTML version deleted]]

I used ?image function to do that, like below : require(grDevices) # for colours x <- y <- seq(-4*pi, 4*pi, len=27) r <- sqrt(outer(x^2, y^2, "+")) image(x, y, r, col=gray((0:32)/32)) However my next problem to add a color pallet for color description [as shown in following link]. If anyone here tell me how to do that, it will be good for me. Regards, Megh Dal

Hi, Could anyone inform how to perform multi-variate auto regression using the past 't' values for regression in R. I have looked at ARMA provided by DES library and mvr provided by PLS library but could not match them to my requirements. Specifically, I want the following Say I have attributes a1-a4. and the regression equation is as follows: a4(t) =

Dear List, The purpose of this e-mail is to ask about R time series procedures - as a biologist with only basic time series knowledge and about a year's experience in R. I have been using ARIMAX models with seasonal components on seasonal data. However I am now moving on to annual data (with only 34 time points) and understand that ARIMA is not suitable for these shorter time periods - does

This seems like a FAQ, but I can't figure it out. I have a mv ts object: R > tsp(pg) [1] 1982 2003 1 R > dim(pg) [1] 22 12 and a univariate ts: R > tsp(rw) [1] 1690 1996 1 Yet, when I try to intersect them: R > tsp(ts.intersect(rw, pg)) [1] 1982 2176 1 the process goes awry. How to I get rw and pg to be one ts that runs from 1982 to 1996 and has 13 univariate time

Hello! Recently I got report that my package mar1s doesn't pass checks any more on R 3.0.2. I started to investigate and found the following difference in multivariate time series handling in R 3.0.2 compared to R 2 (I've checked on 2.14.0). Suppose I wish to calculate seasonal component for time series. In case of multivariate time series, I wish to process each column independently.

This message is in MIME format --_=XFMail.1.3.p0.Linux:990702182137:16900=_ Content-Type: text/plain; charset=us-ascii There was some discussion a while back on R-devel between Ross Ihaka, Paul Gilbert and myself about row subsetting in time series. I think the consensus was that "[.ts" should not try to coerce its result back to a time series object (which is underlying the problem

This looks like a slightly different problem then the other ones: R : Copyright 1999, The R Development Core Team Version 0.64.1 (May 8, 1999) ... > z <- ts(matrix(c(1:9,NA), 5, 2), start=c(1991,1)) > na <- is.na(z) > z[na] Error: subscript (10) out of bounds, should be at most 5 > Paul -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel

>>>>> On Fri, 02 Jul 1999, Adrian Trapletti <Adrian.Trapletti@wu-wien.ac.at> said: Adrian> There seems to be a problem with plot.ts (R Version 0.64.2) > x<-cbind(1:10,2:11) > x<-as.ts(x) > plot(x) Adrian> Error: subscript (20) out of bounds, should be at most 10 This is definitely a bug --> CC: R-bugs ALL NOTE : This is *not* new