similar to: acf?

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

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.

Hello, I am trying to calculate the autocovariance matrix for any general farima(p,d,q) with p,q > 1. Could anyone give an idea how to implement in R or if there is any package for this? thank you beforehand. Jose.

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

Hi, I'm trying to obtain confidence intervals for auto and cross correlation estimates. I've adapted code made available by Stock and Watson that uses the Bartlett Kernel and the delta method. In R it runs really, really slow because of the loops it uses and I have 9 series that I'd like to examine (81 total combinations). It was easy enough to replace one of the while loops with a

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 function, acf(x) and an error message popped up as: Error in .C("acf", as.double(x), as.integer(sampleT), as.integer(nser), :

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

In the R Document, the usage of the acf() is as follow: acf(x, lag.max = NULL, type = c("correlation", "covariance", "partial"), plot = TRUE, na.action = na.fail, demean = TRUE, ...) But now I want to get the result picture like: plot(x,type="l") or plot(x,type="p") How can I do this with acf function? 仭仭仭仭仭仭仭仭仭仭仭仭仭仭仭仭佒伮 伬侎仯仭

I am working with amino acid sequences changing each letter to numbers.I have a data from acf transformation called Zm as shown below. I would like to get Indices D1 to D10 and then create F1 to F10 as indicated below. Is there anyway I can do that in R without typing each of them one by one. For example to get D1 to D3, I have to type D1<-c(Zm[[1]])[1][[1]], D2<-c(Zm[[2]])[1][[1]], and

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

Hello expeRts, I need generate symbolize the autocovariances matrix of a Gaussian ARMA(1,1), for derivate it and evaluate. I try this codes, but whitout sucess vacv<-NULL vacv[1]<-1-2*phi*theta-theta^2 vacv[2]<-(1-phi*theta)*(phi-theta) vacv[3:n]<-acv[2]*(phi^(1:(n-2))) facv<-list() for(i in 1:2)

  Hi r-users,   I would like to use gev and my data (annual rainfall ) is as follows:   > head(dat,20) A B C D E F G H I J 1 45.1 41.5 58.5 50.1 46.0 49.1 37.7 49.1 59.8 54.0 2 50.3 39.8 49.4 56.4 49.4 48.8 42.1 49.8 49.4 58.3 3 41.7 39.3 44.6 39.1 35.7 41.5 40.8 40.8 38.5 45.6 4 50.7 33.9 48.4 28.2 35.5 39.1 61.4 17.0 30.7 38.3 5 39.3 30.6 46.9 23.8 25.8

Hello, I teach statistics and use R Commander for teaching. I have 2 students out of 169 that can't get scatterplots or plot to work. I have had them update packages, restart R/R Commander/their computers and even reinstall R/R Commander. One is using Windows 7 on a new pc and the other is a pc user (not sure the OS). They are both using R2.11.1 and R Commander 1.6-0. The data look like

Dears Sirs During my computational work I encountered unexpected behaviour when calling "ar" function. I want to select the order p of the autoregressive approximation by AIC criterion and sometimes an error occurs. Example: # time series

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

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

I am a new user of R package and I needed a help regarding plotting confidence limits for FFT ( chisquare based) and spectrum using the monte carlo simulations of background red noise . How do I do it in R can any one help in this issue? sudheer º¤ø,¸¸,ø¤º°`°º¤ø,¸¸,ø¤º°`°º¤ø,¸¸,ø¤º°`°º¤º¤ø,¸¸,ø¤º Sudheer Joseph Scientist Indian National Centre for Ocean Information Services

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