R-users
Kunio takezawa wrote:
R-users
E-mail: r-help at r-project.org
I have a quenstion on "gam()" in "gam" package.
The help of gam() says:
'gam' uses the _backfitting
algorithm_ to combine different smoothing or fitting methods.
On the other hand, lm.wfit(), which is a routine of gam.fit() contains:
z <- .Fortran("dqrls", qr = x * wts, n = n, p = p, y = y *
wts, ny = ny, tol = as.double(tol), coefficients = mat.or.vec(p,
ny), residuals = y, effects = mat.or.vec(n, ny), rank = integer(1),
pivot = 1:p, qraux = double(p), work = double(2 * p),
PACKAGE = "base")
It may indicate that QR decomposition is used to derive an additive model
instead of backfitting.
I am wondering if my guess is correct, or this "the _backfitting
algorithm"
has another meaning.
Please don't ask the same question multiple times! And no, backfitting and QR are unrelated concepts. You need to read up on the theory, there are two fundamental books: Hastie & Tibshirani (gam package) and Simon Wood (mgcv package). Both are a bit much to ask to have summarized in email.
O__ ---- Peter Dalgaard ?ster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907