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I am trying to understand the function acf stats:::acf shows me the function I am having trouble understanding the usage "$acf" in the following acf <- array(.C(R_acf, as.double(x), as.integer(sampleT), as.integer(nser), as.integer(lag.max), as.integer(type == "correlation"), acf = double((lag.max + 1L) * nser * nser), NAOK =

Please pardon me if you see this message twice. The mail server has a bit problem. ***************************************************** Hello! I have two questions. First of all, I have a problem dealing with acf (Autocovariance function) and need help. First I defined a time series, x, which is a vector created by x <- ts(rnorm(200)). So I plugged the series directly into the acf

Hi guys, I'm trying to do the autocovariance of a moving average but it's giving me errors. Here is my code: > w=rnorm(500,0,1) > v=filter(w, sides=2, rep(1/3,3)) > acf(w, lag.max=20) <=that printed out a nice graph. > acf(v, lag.max=20) Error in na.fail.default(as.ts(x)) : missing values in object thanks a lot. -- View this message in context:

If first fit my data column V1 to column V2 using normal "lm" fitting, call it "fit1", then I used "acf(fit1$residuals, type='cov', 40) " function to obtain the autocovariance of the residuals, and then constructed a autocovariance matrix, I chose it to be 40x40. Call this autocovariance matrix B, I then use the following "lm.gls" function to

I started to check what I thought I knew with autocovariance and it doesn’t jive with the the calculations given by ‘R’. I was wondering if there is some scaling or something that I am not aware of. Take the example Ø d <- 1:10 Ø (a <- acf(d, type="covariance", demean=FALSE, plot=FALSE)) Autocovariances of series ‘d’, by lag 0 1 2 3 4 5 6

I'm a PhD student and I'm working with covariance function. I'm interested to know if exist some packages in R to calculate and plot the bidimensional Autocovariance Function. the input matrix is a matrix that describe a spatial location over a 2-D space and I want to use it in the same way I can use a time serie in the 1-D acf. Thanks, Nicola.

I'm a PhD student and I'm working with covariance function. I'm interested to know if exist some packages in R to calculate and plot the bidimensional Autocovariance Function. the input matrix is a matrix that describe a spatial location over a 2-D space and I want to use it in the same way I can use a time serie in the 1-D acf. Thanks, Nicola.

Hi! I just installed R on my computer, and I don't manage to run the function acf (autocovariance and autocorrelation function). It says me that this function is unknown. However, the standard functions like cos or read.table are OK. Can someone help me please? Thanks a lot. Naime -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

I have been trying to get a working version of ar, since I have used it in several calculations in the test suite for my time series library. The following limited version (order.max must be specified and other short comings) works more or less, but the results differ by more than I would expect from those given by Splus. I have tried several variations with no success. If anyone can see a reason

On 11/28/2006 11:50 AM, A.I. McLeod wrote: > Hi Duncan, Hi Ian. > > ccf(x,y) does not explain whether c(k)=cov(x(t),x(t+k)) or d(k)=cov(x(t),x(t-k)) is calculated. The following example demonstrates > that the c(k) definition is used: > ccf(c(-1,1,rep(0,8)),c(1,rep(0,9))) > However S-Plus acf uses the d(k) definition in their acf function. I don't think our code looks

I have just put up a new executable as a replacement for the one in rseptbeta.zip there have only been a few changes; mostly to the menu's. I am about to start on a major overhaul including getting survival to work and grabbing the 0.60 version once it's stable. Please let me know about other enhancements you want.... robert

I have just put up a new executable as a replacement for the one in rseptbeta.zip there have only been a few changes; mostly to the menu's. I am about to start on a major overhaul including getting survival to work and grabbing the 0.60 version once it's stable. Please let me know about other enhancements you want.... robert

Full_Name: Ian McLeod Version: 2.3.1 OS: Windows Submission from: (NULL) (129.100.76.136) > There is a simple bug in acf as shown below: > > z <- 1 > acf(z,lag.max=1,plot=FALSE) > Error in acf(z, lag.max = 1, plot = FALSE) : > 'lag.max' must be at least 1 > This is certainly a bug. There are two problems: (i) the error message is wrong since lag.max is

Hi I'm getting the following error that do not make sense to me, what am Idoing wrong ? > acf(Recsim[1,], lag.max=1) Error in acf(Recsim[1, ], lag.max = 1) : 'lag.max' must be at least 1 Regards EJ

pacf in devel seems by default to return a different number of lags than 1.7.1 for $pacf. I don't see any mention of this in the NEWS file, or any change in the documentation, so I suspect it is and error, though it may be an undocumented improvement. (Newbie question: How is the simplest way to display a function like pacf.default that is not exported from a namespace?) Paul

Hi everyone, now I am trying to finish writing the code (I had asked for assistance on subtracting arrays) This is what I what I am running in R: > source("/home/ie/Documents/TTU/GA_Research/GLUE/R-Project/R_GLUE_Example/NSEr.R") NSEr <- function (obs, sim) { {jjh <- (as.vector(obs) - sim)^2 Xjjhs <- apply(Xjjh, 2, sum) Yii <- (obs - mean(obs))^2 Yiis <- apply(Yii, 2,

It says that nser requires the most recent version of magrittr that you do not have installed. You must update magrittr before attempting to install nser: update.packages(oldPkgs = "magrittr") or at the prompt you were presented before, choose to update magrittr before installing nser. On Sun, Apr 9, 2023, 17:55 akshay kulkarni <akshay_e4 at hotmail.com> wrote: > Dear

Dear members, I can't install "nser" package. It is not in cran but install_version and install_github both are not working: > install_version("nser",version = "1.4.0") Downloading package from url: https://cran.rstudio.com//src/contrib/Archive/nser/nser_1.4.0.tar.gz These packages have more recent versions available. It is

Dear R-project users I would like to calculate a linear trend versus time taking into account a first order autoregressive process of a single time series (e.g. data$S80 in the following example) using th gls function. gls(S80 ~ tt,data=data,corAR1(value, form, fixed)) My question is what number to set in the position of value within corAR1? Should it be the acf at lag 1? I look forward for

Dear all, I have two different data frames, that have two common variables: date and sample. Here is a small extract of both of them > head(traffic) datet sessiont samplet buddleiat 1 07-08-2012 1 1 1 2 07-08-2012 1 1 1 3 07-08-2012 1 1 1 4 07-08-2012 1 2 3 5 07-08-2012 1 2