I use R 3.0.1. #I do have that line after ` lag[lower.tri(lag)] <- -1`
acf <- .Call(C_acf, x, lag.max, type == "correlation") lag <- outer(0:lag.max, lag/x.freq) acf.out <- structure(list(acf = acf, type = type, n.used = sampleT, lag = lag, series = series, snames = colnames(x)), class = "acf") Check this link: http://stackoverflow.com/questions/14035506/how-to-see-the-source-code-of-r-internal-or-primitive-function A.K. ________________________________ From: Cathy Lee Gierke <leegi...@umn.edu> To: arun <smartpink...@yahoo.com> Sent: Tuesday, July 30, 2013 5:04 PM Subject: Re: [R] acf and ccf You must have a different version of R? But you do have a line: acf <- .Call(C_acf, x, lag.max, type == "correlation") That is quite similar. It is a call to a function that does the actual math. Here is what I get: function (x, lag.max = NULL, type = c("correlation", "covariance", "partial"), plot = TRUE, na.action = na.fail, demean = TRUE, ...) { type <- match.arg(type) if (type == "partial") { m <- match.call() m[[1L]] <- as.name("pacf") m$type <- NULL return(eval(m, parent.frame())) } series <- deparse(substitute(x)) x <- na.action(as.ts(x)) x.freq <- frequency(x) x <- as.matrix(x) if (!is.numeric(x)) stop("'x' must be numeric") sampleT <- as.integer(nrow(x)) nser <- as.integer(ncol(x)) if (is.na(sampleT) || is.na(nser)) stop("sampleT and nser must be ints", domain = NA) if (is.null(lag.max)) lag.max <- floor(10 * (log10(sampleT) - log10(nser))) lag.max <- as.integer(min(lag.max, sampleT - 1L)) if (is.na(lag.max) || lag.max < 0) stop("'lag.max' must be at least 0") if (demean) x <- sweep(x, 2, colMeans(x, na.rm = TRUE), check.margin = FALSE) lag <- matrix(1, nser, nser) lag[lower.tri(lag)] <- -1 acf <- array(.C(C_acf, as.double(x), sampleT, nser, lag.max, as.integer(type == "correlation"), acf = double((lag.max + 1L) * nser * nser), NAOK = TRUE)$acf, c(lag.max + 1L, nser, nser)) lag <- outer(0:lag.max, lag/x.freq) acf.out <- structure(.Data = list(acf = acf, type = type, n.used = sampleT, lag = lag, series = series, snames = colnames(x)), class = "acf") if (plot) { plot.acf(acf.out, ...) return(invisible(acf.out)) } else return(acf.out) } <bytecode: 0x7f8e04f34ea8> <environment: namespace:stats> Cathy Lee Gierke On Tue, Jul 30, 2013 at 3:57 PM, arun <smartpink...@yahoo.com> wrote: Hi, >When I type 'acf', I get this: > > >function (x, lag.max = NULL, type = c("correlation", "covariance", > "partial"), plot = TRUE, na.action = na.fail, demean = TRUE, > ...) >{ > type <- match.arg(type) > if (type == "partial") { > m <- match.call() > m[[1L]] <- as.name("pacf") > m$type <- NULL > return(eval(m, parent.frame())) > } > series <- deparse(substitute(x)) > x <- na.action(as.ts(x)) > x.freq <- frequency(x) > x <- as.matrix(x) > if (!is.numeric(x)) > stop("'x' must be numeric") > sampleT <- as.integer(nrow(x)) > nser <- as.integer(ncol(x)) > if (is.na(sampleT) || is.na(nser)) > stop("'sampleT' and 'nser' must be integer") > if (is.null(lag.max)) > lag.max <- floor(10 * (log10(sampleT) - log10(nser))) > lag.max <- as.integer(min(lag.max, sampleT - 1L)) > if (is.na(lag.max) || lag.max < 0) > stop("'lag.max' must be at least 0") > if (demean) > x <- sweep(x, 2, colMeans(x, na.rm = TRUE), check.margin = FALSE) > lag <- matrix(1, nser, nser) > lag[lower.tri(lag)] <- -1 > acf <- .Call(C_acf, x, lag.max, type == "correlation") > lag <- outer(0:lag.max, lag/x.freq) > acf.out <- structure(list(acf = acf, type = type, n.used = sampleT, > lag = lag, series = series, snames = colnames(x)), class = "acf") > if (plot) { > plot.acf(acf.out, ...) > invisible(acf.out) > } > else acf.out >} > > > >I couldn't get: > >array(.C(C_acf, as.double(x), sampleT, nser, lag.max, > as.integer(type == "correlation"), acf = double((lag.max + > 1L) * nser * nser), NAOK = TRUE)$acf, c(lag.max + > 1L, nser, nser)) > > >________________________________ > >From: Cathy Lee Gierke <leegi...@umn.edu> >To: arun <smartpink...@yahoo.com> >Sent: Tuesday, July 30, 2013 4:49 PM > >Subject: Re: [R] acf and ccf > > > > >Thank you. Yes, I supposed that does give you the function. However, most of >the meaningful code is inside another compiled function: > > acf <- array(.C(C_acf, as.double(x), sampleT, nser, lag.max, > as.integer(type == "correlation"), acf = double((lag.max + > 1L) * nser * nser), NAOK = TRUE)$acf, c(lag.max + > 1L, nser, nser)) > >Any idea how to see that? > > >Cathy Lee Gierke > > >On Tue, Jul 30, 2013 at 3:28 PM, arun <smartpink...@yahoo.com> wrote: > >Just type >>acf >>ccf >>on R prompt >>A.K. >> >> >> >> >> >> >>----- Original Message ----- >>From: Cathy Lee Gierke <leegi...@umn.edu> >>To: r-help@r-project.org; r-core-ow...@r-project.org >>Cc: >>Sent: Tuesday, July 30, 2013 4:02 PM >>Subject: [R] acf and ccf >> >>Greetings, >> >>Is it possible to see the source code for the acf and ccf functions? I >>want to understand the exact formula used. >> >>It may be in this book, but I am hoping I can find it elsewhere, as the >>book is quite expensive. >>Venables, W. N. and Ripley, B. D. (2002) *Modern Applied Statistics with S*. >> >>Fourth Edition. Springer-Verlag. >> >> >>Sincere thanks, >>Cathy Lee Gierke >> >> [[alternative HTML version deleted]] >> >>______________________________________________ >>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. >> >> > ______________________________________________ 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.
