Hi Michael,
How about,
x <- x[, colnames(x) != "(Intercept)"]
I hope this helps,
John
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On Behalf Of Michael Friendly
> Sent: Tuesday, January 29, 2013 8:45 AM
> To: R-help
> Subject: [R] how to suppress the intercept in an lm()-like formula
> method?
>
> I'm trying to write a formula method for canonical correlation analysis,
> that could be called similarly to lm() for
> a multivariate response:
>
> cancor(cbind(y1,y2,y3) ~ x1+x2+x3+x4, data=, ...)
> or perhaps more naturally,
> cancor(cbind(y1,y2,y3) ~ cbind(x1,x2,x3,x4), data=, ...)
>
> I've adapted the code from lm() to my case, but in this situation, it
> doesn't make sense to
> include an intercept, since X & Y are mean centered by default in the
> computation.
>
> In the code below, I can't see where the intercept gets included in the
> model matrix and therefore
> how to suppress it. There is a test case at the end, showing that the
> method fails when called
> normally, but works if I explicitly use -1 in the formula. I could hack
> the result of model.matrix(),
> but maybe there's an easier way?
>
> cancor <- function(x, ...) {
> UseMethod("cancor", x)
> }
>
> cancor.default <- candisc:::cancor
>
> # TODO: make cancisc::cancor() use x, y, not X, Y
> cancor.formula <- function(formula, data, subset, weights,
> na.action,
> method = "qr",
> model = TRUE,
> x = FALSE, y = FALSE, qr = TRUE,
> contrasts = NULL, ...) {
>
> cl <- match.call()
> mf <- match.call(expand.dots = FALSE)
> m <- match(c("formula", "data", "subset", "weights", "na.action"),
> names(mf), 0L)
> mf <- mf[c(1L, m)]
>
> mf[[1L]] <- as.name("model.frame")
> mf <- eval(mf, parent.frame())
>
> mt <- attr(mf, "terms")
> y <- model.response(mf, "numeric")
> w <- as.vector(model.weights(mf))
> if (!is.null(w) && !is.numeric(w))
> stop("'weights' must be a numeric vector")
>
> x <- model.matrix(mt, mf, contrasts)
> # fixup to remove intercept???
> z <- if (is.null(w))
> cancor.default(x, y, ...)
> else stop("weights are not yet implemented") # lm.wfit(x, y, w,
> ...)
>
> z$call <- cl
> z$terms <- mt
> z
> }
>
> TESTME <- FALSE
> if (TESTME) {
>
> # need to get latest version, 0.6-1 from R-Forge
> install.packages("candisc", repo="http://R-Forge.R-project.org";)
> library(candisc)
>
> data(Rohwer)
>
> # this bombs: needs intercept removed
> cc <- cancor.formula(cbind(SAT, PPVT, Raven) ~ n + s + ns + na + ss,
> data=Rohwer)
> ## Error in chol.default(Rxx) :
> ## the leading minor of order 1 is not positive definite
>
> #this works as is
> cc <- cancor.formula(cbind(SAT, PPVT, Raven) ~ -1 + n + s + ns + na +
> ss, data=Rohwer)
> cc
> ## Canonical correlation analysis of:
> ## 5 X variables: n, s, ns, na, ss
> ## with 3 Y variables: SAT, PPVT, Raven
> ##
> ## CanR CanRSQ Eigen percent cum
> ## 1 0.6703 0.44934 0.81599 77.30 77.30
> ## 2 0.3837 0.14719 0.17260 16.35 93.65
> ## 3 0.2506 0.06282 0.06704 6.35 100.00
> ##
> ## Test of H0: The canonical correlations in the
> ## current row and all that follow are zero
> ##
> ...
> }
>
>
> --
> Michael Friendly Email: friendly AT yorku DOT ca
> Professor, Psychology Dept. & Chair, Quantitative Methods
> York University Voice: 416 736-2100 x66249 Fax: 416 736-5814
> 4700 Keele Street Web: http://www.datavis.ca
> Toronto, ONT M3J 1P3 CANADA
>
> ______________________________________________
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