similar to: interpreting acf plot

Hi R users, where can I find the equations used by acf function to calculate autocorrelation? I think I misunderstand acf. Doesn't acf use following equation to calculate autocorrelation? [image: R(\tau) = \frac{\operatorname{E}[(X_t - \mu)(X_{t+\tau} - \mu)]}{\sigma^2}\, ,] If it does, then the autocorrelation of a sine function should give a cosine; however, the following code gives a

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'

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.

When I run the "acf()" function using the "acf(ts.union(mdeaths, fdeaths))" example, the "acf()" function calls the "acf.plot()" function to generate this plot... http://members.cox.net/ddebarr/images/acf_example.png The plot in the lower right-hand corner is labeled "fdeaths & mdeaths", but the negative lags appear to belong to "mdeaths

Hi List, I'm trying to calculate the autocorrelation coefficients for a time series using acf at various lags. This is working well, and I can get the coefficients without any trouble. However, I don't seem to be able to obtain the significance of these coefficients from the returned acf object, largely because I don't know where I might find them. It's clear that the acf

Dear all, I have one Model (M3) fitted using the lme package, and I have checked the correlation structure of within-group errors using plot(ACF (M3,maxLag=10),alpha=0.05) But now I am not sure how to interpret this plot for the empirical autocorrelation function. The problem is that I am used to see/interpret diagrams in which all the autocorrelation Lags, except lag-1, are inside the

Hi everyone, I've got a question concerning the function acf(.) in R for calculating the autocorrelation in my data. I have a table with daily returns of several stocks over time and I would like to calculate the autocorrelation for all the series (not only for one time series). How can I do this? After that I want to apply an autoregressive model based on the estimated lag in the

Hi R-sters, Just wondering what I might be doing wrong. I'm trying to fit a multiple linear regression model, and being ever mindful about the possibilities of autocorrelation in the errors (it's a time series), the errors appear to follow an AR1 process (ar(ts(glsfit$residuals)) selected order 1). So, when I go back and try to do the simultaneous regression and error fit with gls,

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 everyone, I'm trying to use the acf() function to calculate the autocorrelation of each column in a matrix. The trouble is that I can only seem to get the function to work if I extract the data in the column into a separate matrix and then apply the acf() function to this column. I have something like this: acf(mat,lag.max=10,na.action=na.pass) ...but I would really like to apply the

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 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....

Hi there, I have R 0.64.2. I wonder if this R has acf function to calculate autocorrelation? since the help(acf) doesnt seem to be able to help me. thanks, Peppy -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the

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

Hello r-help, I have a couple of time-series of different length and I would like to produce a simple overview plot showing the autocorrelation functions of the series. The time-series are stored in a dataframe like this: > test.data item year value 1 xxx 1961 -1.09 2 xxx 1962 0.21 3 xxx 1963 -0.81 [trimmed] 8

Hi list, I've been producing autocorrelation functions of time series using the acf function, and have found a series or two for which correlations of > 1 are given, which I think shouldn't happen. Attached is the time series I'm using, and below is the R code (version 2.9.1) that I'm entering: series <- read.csv("series.csv") corr <- acf(series, lag.max=90,

Hi R lovers! I'd like to know if the 2 blue lines in the graph produced by the function acf in the package ts represents the level for the test of significance of the autocorrelation thanks for help vincent ****************************************************************** The sender's email address has changed to firstname.lastname@ sgcib.com. You may want to update your

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,]

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

At Mon, 19 Nov 2001 08:36:38, you wrote: > I get the labels I expect: if this is quarterly data the lags are labelled > in years. That is what `frequency = 4' is intended to mean: 4 > observations per unit of time. some further thoughts convinces me that this is a mis-feature. if you ask any person what is the lag i autocorrelation, the answer would be corr(y_t, y_{t-i}). so you