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"

zoo overcomes many of the limitations of ts: library(zoo) as.ts(head(as.zoo(presidents))) ## Qtr1 Qtr2 Qtr3 Qtr4 ## 1945 NA 87 82 75 ## 1946 63 50 xts also works here. On Sun, Jun 9, 2024 at 12:04?PM Spencer Graves <spencer.graves at prodsyse.com> wrote: > > Hello, All: > > > The 'head' and 'tail' functions strip the time

Hi, Gabor et al.: Thanks for this. I should change my current application to use either zoo or xts, as Gabor suggests. However, I was surprised to learn that "[.ts" does NOT return an object of class "ts". I see that "head.default" and "head.matrix" both call "[", so "head" cannot return a ts object, because "["

Hello, All: The 'head' and 'tail' functions strip the time from a 'ts' object. Example: > head(presidents) [1] NA 87 82 75 63 50 > window(presidents, 1945, 1946.25) Qtr1 Qtr2 Qtr3 Qtr4 1945 NA 87 82 75 1946 63 50 Below please find code for 'head.ts' and 'tail.ts' that matches 'window'. Comments?

It isn't really clear that it can't work. This does work by inserting NA's. library(zoo) as.ts(as.zoo(lynx)[ c(1:3, 7) ] ) ## Time Series: ## Start = 1821 ## End = 1827 ## Frequency = 1 ## [1] 269 321 585 NA NA NA 3928 On Mon, Jun 10, 2024 at 10:32?AM Martin Maechler <maechler at stat.math.ethz.ch> wrote: > > >>>>> Spencer Graves

Hi, Martin et al.: On 6/10/24 9:32 AM, Martin Maechler wrote: >>>>>> Spencer Graves >>>>>> on Mon, 10 Jun 2024 07:50:13 -0500 writes: > > > Hi, Gabor et al.: Thanks for this. I should change my > > current application to use either zoo or xts, as Gabor > > suggests. > > > > However, I was

>>>>> Spencer Graves >>>>> on Mon, 10 Jun 2024 07:50:13 -0500 writes: > Hi, Gabor et al.: Thanks for this. I should change my > current application to use either zoo or xts, as Gabor > suggests. > However, I was surprised to learn that "[.ts" does NOT > return an object of class "ts". I see that

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) =