similar to: Bug in acf function?

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 =

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

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

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,

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

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'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

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

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

Dear users, I have two continuous variables which are two different measures taken each year from 1975 to 2005. I want to see if the two variables are correlated but need to take into account the fact that they are a time series. I have been following an example from 'The R Book' where you plot the ACF: par(mfrow=c(1,1) acf(cbind(x,y)) and this appeared to work fine, producing four

Hi, I noticed that whenever I ran acf or pacf, the plot generated by R always includes two horizontal blue doted lines. Furthermore, these two lines are not documented in the acf documentation. I don't know what they are for, but it seems that they are important. Could someone tell me what they are and how are they calculated? Thanks, -- Tom [[alternative HTML version deleted]]

Hi all, I am modelling a time series with missing data. *Q1)* However, I am not sure if I should use the next *graphics* to understand my data: *a)* ACF & PACF (original series) *b)* ACF & PACF (residuals) * * *Q2)* I am using *tsdiag*, so I obtain a graphic with 3 plots: stand. residuals vs time; acf for residuals; Ljung-Box for residuals (it is wrong for residuals). I know that using

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 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

Hello all, I am trying to use lme to examine how a response variable (Chla) changes over time in different treatments (2 Temp & 2 Light levels). Within each treatment combination, there are two replicate tanks (each with unique TankID) with coral fragments in them. All tanks are subject to the same environment until Time=0, when treatments are imposed, and Chla is measured for each

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'

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 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

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,]

Hello, I would like to have some information about acf with missing values. Let us consider this example: x=rnorm(100) x2=x x2[sample(100,10)]=NA acf1=acf(x) acf2=acf(x2,na.action=na.pass) The computation of the acf is different for the two data sets. Looking at the the code reveals that with missing values, the computation of acf takes into account the number of pairs of non-NA values (i.e.