similar to: acf Significance

Hi, Im new to R so this question is quite fundamental. Im trying to compare some autocorrelations generated by the acf function to some theoretical correlations. How can I have acces to just the autocorrelations, for computation? This is some of my code: > acf.data<-c(acf(x)) > acf.data This is the R output: $acf , , 1 [,1] [1,] 1.000000000 [2,]

Hi, I would like to use acf.plot on a correlogram that is computed externally. In other words, I would like to "fake out" the acf object. Is this possible?-- any help would be appreciated. TIA Martin

This is not exactly an R question but the R code below may make my question more understandable. If one plots sin(x) where x runs from -pi to pi , then the curve hovers around zero obviously. so , in a"stationary in the mean" sense, the series is stationary. But, clearly if one plots the acf, the autocorrelations at lower lags are quite high and, in the "box jenkins"

Dear all, I have an annual time-series of population numbers and I would like to estimate the auto-correlation. Can I use acf() function and judge whether auto-correlation is significant by the plots? The acf array, eg: Autocorrelations of series 'x$log.s.r', by lag 0 1 2 3 4 5 6 7 8 9 10 11 12 1.000 0.031 -0.171

Dear all, given two numeric vectors x and y, the ACF(x) at lag k is cor(x(t),x(t+k)) while the CCF(x,y) at lag k is cor(x(t),y(t-k)). See below for a simple example. > set.seed(1) > x <- rnorm(10) > y <- rnorm(10) > x [1] -0.6264538 0.1836433 -0.8356286 1.5952808 0.3295078 -0.8204684 0.4874291 0.7383247 0.5757814 -0.3053884 > y [1] 1.51178117 0.38984324

Hi list, I have the following code to compute the acf of a time series acfresid <- acf(residfit), where residfit is the series when I type acfresid at the prompt the follwoing is displayed Autocorrelations of series ?residfit?, by lag 0.0000 0.0833 0.1667 0.2500 0.3333 0.4167 0.5000 0.5833 0.6667 0.7500 0.8333 1.000 -0.015 0.010 0.099 0.048 -0.014 -0.039 -0.019 0.040 0.018

Dear R list As suggested by Prof Brian Ripley, I have tried to read acf literature. The main problem is I am not the statistician and hence have some problem in understanding the concepts immediately. I came across one literature (http://www.stat.nus.edu.sg/~staxyc/REG32.pdf) on auto-correlation giving the methodology. As per that literature, the auto-correlation is arrived at as per following.

Hi R, I have doubt. >x= c(4,5,6,3,2,4,5) >acf(x,plot=F,lag.max=1) Autocorrelations of series 'x', by lag 0 1 1.000 0.182 But if I actually calculate the autocorrelation at lag1 I get, >cor(x[-1],x[-length(x)]) [1] 0.1921538 Even in excel I get 0.1921538 value. So, I want to know what the 'acf' function is calculating here....

I am guessing this is a very simple question, but this is only my second day with R so it is all still a bit imposing. I am trying to run an autocorrelation. I imported a CSV file, which has one column labeled "logistic". I ran the command: ACF(data$logistic,maxLag=10) However, I received the error: Error in UseMethod("ACF") : no applicable method for 'ACF'

I need to modify the graph of the autocorrelation. I tried to do it through plot.acf but with no success. 1. I would like to get rid of the lag zero 2. I would like to have numbers on the x-axis only at lags 12, 24, 36, 48, 60, ... Could anybody help me in this? Any help will be appreciated Thank you for your attention Stefano [[alternative HTML version deleted]]

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

Hi all, I am getting different results from ccf and cor, Here is a simple example: set.seed(100) N <- 100 x1 <- sample(N) x2 <- x1 + rnorm(N,0,5) ccf(x1,x2)$acf[ccf(x1,x2)$lag == -1] cor(x1[-N], x2[-1]) Results: > ccf(x1,x2)$acf[ccf(x1,x2)$lag == -1] [1] -0.128027 > cor(x1[-N], x2[-1]) [1] -0.1301427 Thanks, Tal ----------------Contact

Hello all, I found a funny problem with y-axis labels when plotting acf(matrix) - the labels are too close to one of the margins and cut in half. Here's the problem: test<-matrix(rnorm(200),ncol=4) acf(test) This doesn't fix the problem: test<-matrix(rnorm(200),ncol=4) par(mar=c(3,3,2,0.2),oma=c(0,0,0,0)) acf(test) This does fix the margin. I understand why, but not sure why ONLY

Hello, I was wondering if anybody could help me with this? I have plotted an acf function for a time series and am very happy with it. Now I am interested in calculating for myself the two values for the confidence intervals that are plotted on the graph of the acf. The confidence intervals do not appear to be returned from the acf function (is this true?). So far I haven't managed to

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 =

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, Can anyone please provide the formula used to compute ACF(nlme). I believe the one that is used in R is of the type mentioned on the website. Please correct me if I am wrong. The normalization of the numerator (Ch) has been done by 'N' where as I would like to do it by 'N-k'. Is there anyway in the present implementation of ACF to normalize it by 'N-k', where

Hi, I'm plotting 5 autocorrelation plots on one page. Using par(mfrow=c(3,2)) everything comes out fine. However, for each plot, it prints a title on top of each plot that says Series followed by the variable name used in the plot. I want to suppress those titles, but I also want a general figure title on the bottom of the page. I've looked at the Murrell book as well as the acf

Hi, I don't quite understant how can I access to the acf values from the list produced by the acf function Example: library(ts) t <- acf(ts.union(ts(1:10), ts(11:20))) t$acf > tmp$acf , , 1 [,1] [,2] [1,] 1.00000000 1.00000000 [2,] 0.70000000 0.70000000 [3,] 0.41212121 0.41212121 [4,] 0.14848485 0.14848485 [5,] -0.07878788 -0.07878788 [6,] -0.25757576

Hola, Estoy visualizando una serie temporal para determinar sus órdenes ARIMA y no consigo lo siguiente: ¿Cómo puedo sacar la ACF de los retardos múltiplos del periodo? Es decir, sólo ver en el gráfico ACF los retardos 12, 24, 36... Gracias!! David [[alternative HTML version deleted]]