Thanks to Prof. Ripley and Phil Spector for pointing out that the autocorrelation functions must use a "nontraditional" definition of the covariance, involving a denominator of n (instead of n-1) in order to satisfy an assumption of second-order stationarity in the (unbiased) covariance estimators of a time series.
In terms of getting at the source code for the (apparently compiled) "R_acf", however, I've had no luck. While https://svn.r-project.org/R/trunk seems to be able to show me the source code for otherwise obscured (in the R console) functions like print() (e.g. https://svn.r-project.org/R/trunk/src/library/base/R/print.R ), I can't seem to find the C code ("R_acf"?) called in this section: .... 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 + 1) * nser * nser), NAOK = TRUE) .... of acf(). For instance, in https://svn.r-project.org/R/trunk/src/library/stats/src/ there is (seemingly) no "R_acf.C" or "stats.C" file that I would expect to see. I apologize in advance if this question is elementary or naive -- this is my first time dealing with the source code. Thanks again. --Bob Farmer On Wed, Apr 23, 2008 at 3:31 PM, Prof Brian Ripley <[EMAIL PROTECTED]> wrote: > On Wed, 23 Apr 2008, Bob Farmer wrote: > > > > Hi. > > It's my understanding that a cross-correlation function of vectors x > > and y at lag zero is equivalent to their correlation (or covariance, > > depending on how the ccf is defined). > > > > The ratio of your values is > > > > MASS::fractions(282568.5/259021) > > > [1] 12/11 > > ? Do you recognize it? > > There is an explanation in MASS4, p. 390, for example. > > > > > If this is true, could somebody please explain why I get an > > inconsistent result between cov() and ccf(type = "covariance"), but a > > consistent result between cor() and ccf(type = "correlation")? > > Or have I misunderstood what is a cross-correlation? > > (unfortunately, I can't seem to get a look at the ccf code, since I > > think it's buried in some C function outside of the main environment) > > > > It is in the R sources, not 'buried' at all - that is what 'Open Source' > means. You can browse them at https://svn.r-project.org/R/trunk, or download > them for study. > > > > > > > Thanks very much. > > --Bob Farmer > > PhD candidate, Dalhousie University > > Halifax, NS, Canada > > > > Example: > > d1<-data.frame(matrix(ldeaths, nrow = 6, byrow = T)) > > seventy_4<-as.numeric(d1[1,]) > > seventy_5<-as.numeric(d1[2,]) > > > > ccf(x=seventy_4, y=seventy_5, > > plot = F, lag.max = 0, type = "covariance" > > ) > > cov(seventy_4, seventy_5) #inconsistent > > > > ccf(x=seventy_4, y=seventy_5, > > plot = F, lag.max = 0, type = "correlation" > > ) > > cor(seventy_4, seventy_5) #consistent > > > > > > ______________________________________________ > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > > > -- > Brian D. Ripley, [EMAIL PROTECTED] > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > University of Oxford, Tel: +44 1865 272861 (self) > 1 South Parks Road, +44 1865 272866 (PA) > Oxford OX1 3TG, UK Fax: +44 1865 272595 > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
