similar to: Confidence intervals in ccf()

Hi, I have missing values in my time series. "na.action = na.pass" works for acf and pacf. Why do I get the following error for the ccf? > ts(matrix(c(dev$u[1:10],dev$q[1:10]),ncol=2),start=1,freq=1) Time Series: Start = 1 End = 10 Frequency = 1 Series 1 Series 2 1 68.00000 138.4615 2 70.00000 355.5556 3 68.76000 304.3200 4 68.00000 231.4286 5 69.74194 357.4963 6

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

Dear All, I am studying some process measurement time series in R and trying to identify time delays using cross-correlation function ccf. The results have however been bit confusing. I found a couple of years old message about this issue but unfortunately wasn't able to find it again for a reference. For example, an obvious time shift is observed between the measurements y1 and y2 when the

I am trying to run a cross-correlation using the "ccf()" function. When I select plot = TRUE in the ccf() I get a graph which has ACF on the y-axis, which would suggest that these y-values are the auto-correlation values. How should I adjust the code to produce a plot that provides the cross-correlation values? Here is my code: w002dat <-

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

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

im using R 1.5.0 on redhat. when i use ccf in the ts library i get, what i think is, an incorrect entry in the lag and acf components. as an example, look at the second entry in the lag and acf components below: > library(ts) > tmp <- ccf(ts(rnorm(3)),ts(rnorm(3)),plot=F) > tmp$lag , , 1 [,1] [1,] -1 [2,] 0 [3,] 0 [4,] 1 > tmp$acf , , 1 [,1] [1,]

Hi everyone, When the CCF between two series of observations is plotted in R, a line indicating (presumably) the significance threshold appears across the plot. Does anyone know how this threshold is determined (it is different for each set of series) and how its value can be extracted from R? I've tried saving the CCF into an object and unclassing the object, but there's nothing there to

Hello, I am a very new R user and not a statistician so please excuse any over explanation, I'm just trying to be as clear as possible. I have performed a cross correlation of two time series (my columns) in a single data setusing: ccf(ts(A[rows,columnX]),(A[rows,columnY]), lag=NULL, type="correlation",plot=F) I?am able to get the results (for example): Autocorrelations of

Hello, If I have a character string like d <- c("1990m3", "1992m8") #March 1990 and Aug 1992 what is the easiest way to convert it into any standard date form; for example, d <- c("01/03/1990", "01/08/1992") I looked at as.Date but it doesn't seem to address my problem as I have an "m" stuck in the middle of my character string

Hello everybody, I am sorry if my questions are too simple or not easily understandable. I’m not a native English speaker and this is my first analysis using this function. I have a problem with a cross correlation function and I would like to understand how I have to perform it in R. I have yearly data of an independent variable (x) from 1982 to 2010, and I also have yearly data of a variable

Dear ladies and gentlemen, I would like to calculate autocovarinace and cross-covariance scores 1, 2 and 3 of four classes A, B, C and D. I am using acf and ccf from time sires library. My problem is that I can not separate my data among the classes A, B, C and D. When I calculated acf for Score 1, I got a wrong result. The reason being that instead of using ony 60, 40 and 20, the program

Hi, How do I check for two conditions in an if loop? I want to check if a value lies between 2 other values. For example, A <- ts(rnorm(120), freq=12, start=c(1992,8)) X <- 0.5 Y <- 0.8 I would like to create a new vector C for which C[i] is 0 if A[i] lies in between X and Y. Would be grateful for any help. Sorry for asking such an R-newbie question! Shruthi -- View this message

Dear R-users, I have been using R and its core-packages with great satisfaction now for many years, and have recently started using the "ccf" function (part of the "stats" package version 2.16.0), about which I have a question. The "ccf"-algorithm for calculating the cross-correlation between two time series always calculates the mean and standard deviation per time

I ran across this problem when playing with ccf(). Its function call is >function (x, y, lag.max = NULL, type = c("correlation", "covariance"), plot = TRUE, na.action = na.fail, ...) Internally, ccf() calls plot(), which digs up plot.acf() whose default style is type='h' . I wanted to pass the argument type='l' to the plotting routine, but of

Hi, How can one ask getSymbols to obtain data within a specified time interval? For example, if I am downloading US PPI data: usppi <- as.zoo(getSymbols("PPIACO", src="FRED", verbose=TRUE, auto.assign=FALSE)) How do I ask getSymbols to truncate starting from Jan-1970 until present? I looked up the help file but couldn't find anything. Another newbie question, can I

Hi, I have a simple linear regression for which I want to obtain HAC corrected standard errors, since I have significant serial/auto correlation in my residuals, and also potential heteroskedasticity. Would anyone be able to direct me to the function that implements this in R? It's a basic question and I'm sure I'm missing something obvious here. I looked up this post:

I have two date objects X <- c("01-03-1993", "01-05-1997") #Mar 1993 and May 1997 Y <- c("01-02-1995", "01-08-1999") #Feb 1995 and Aug 1999 and a time series object A <- ts(rnorm(120), freq=12, start=c(1992,8)) #Aug 1992 to Aug 2002 I want to create a binary (0-1) vector B that is of length 1:(A). B should have value 1 for the time periods

Hi, I'm trying to do PCA on a n by p wide matrix (n < p), and I'd like to get more principal components than there are rows. However, svd() only returns a V matrix of with n columns (instead of p) unless the argument nv=p is set (prcomp calls svd without setting it). Moreover, the eigenvalues returned are always min(n, p) instead of p, even if nv is set: > x <-

hello, i have been using ccf() to look at the correlation between lightning and electrogamnetic data. for the most part it has worked exactly as expected. however, i have come across something that puzzles me a bit: > x <- c(1, 0, 1, 0, 1, 0) > y <- c(0, 0, 0, 0, 0, 0) > ccf(x, x, plot = FALSE) Autocorrelations of series 'X', by lag -4 -3 -2 -1 0