similar to: modeling time series with ARIMA

Dear all R users, I am really struggling to determine the most appropriate lag order of ARIMA model. My understanding is that, as for MA [q] model the auto correlation coeff vanishes after q lag, it says the MA order of a ARIMA model, and for a AR[p] model partial autocorrelation vanishes after p lags it helps to determine the AR lag. And most appropriate model choosed by this argument gives

Good afternoon! I'm trying to model a ts but unfortunately i'.m very new to this kind of modeling so i 'll be very grateful if you have an advice. This was my syntax:

I have to say... since it''s bugged me _many_ times, that i *hate* these text boxes with the sliders that are being used to display text (for instance, on Rails documentation pages... but it''s not just Rails). Very often you can''t really read the text because it goes past the right border of the box. So you have to go to the bottom of the box to move the slider to

Dear R help, I have some readings in three dimensions (x, y, z) and an amplitude for each. I'd like to visualize the data using ggplot, using tile plots, as I have some additional point data I would like to eventually overlay on the tile plots. I would like to subset the data by sections, slices if you will, in the z dimension, and plot the data for that slice. I can do all of this, but am

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]]

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 =

I've created a dataframe containing multiple ACF lists through the command rev.acf<-apply(rev.matrix, 2, acf, na.action=na.contiguous, lag.max=12, plot=FALSE) where rev.matrix is an n by t matrix containing n time series in columns. I'd now like to pull out only the ACF information and store it in a seperate n by 12 matrix. So far the only way I can work out to access this is

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 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 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'

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

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 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 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

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

How can I make sure the residual signal, after subtracting the trend extracted through some technique, is actually trend-free ? I would greatly appreciate any suggestion about some Stationarity tests. I'd like to make sure I have got the difference between ACF and PACF right. In the following I am citing some definitions. I would appreciate your thoughts. ACF(k) estimates the correlation

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

(Moved from r-devel to r-bugs) On 3/24/2006 5:03 AM, Antonio, Fabio Di Narzo wrote: > Hi all. > There's a bug in plot.acf, when plotting acf for multivariate time series. > Here a reproducible example: > > X <- rnorm(1000) > Y <- -X + rnorm(1000, sd=0.6) > Z <- cbind(X,Y) > > In > acf(Z) > cross-correlation plot y-axis is limited to 0-1. But: >

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

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]]