similar to: R installer can't find math.h, stdio.h

mgcv 1.4 is now on CRAN. It includes new features to allow mgcv::gam to fit almost any (quadratically) penalized GLM, plus some extra smoother classes. New gam features ------------------------- * Linear functionals of smooths can be included in the gam linear predictor, allowing, e.g., functional generalized linear models/signal regression, smooths of interval data, etc. * The parametric

mgcv 1.4 is now on CRAN. It includes new features to allow mgcv::gam to fit almost any (quadratically) penalized GLM, plus some extra smoother classes. New gam features ------------------------- * Linear functionals of smooths can be included in the gam linear predictor, allowing, e.g., functional generalized linear models/signal regression, smooths of interval data, etc. * The parametric

Dear users, I am trying to show the equation (including coefficients from the model estimates) for a gam model but do not understand how to. Slide 7 from one of the authors presentations (gam-theory.pdf URL: http://people.bath.ac.uk/sw283/mgcv/) shows a general equation log{E(yi )} = ?+ ?xi + f (zi ) . What I would like to do is put my model coefficients and present the equation used. I am an

Just to avoid possible confusion, let me correct a typo (at step [2] in the example below). Apologies! -----FW: <XFMail.111023084327.ted.harding at wlandres.net>----- Date: Sun, 23 Oct 2011 08:43:27 +0100 (BST) Sender: r-help-bounces at r-project.org From: (Ted Harding) <ted.harding at wlandres.net> To: r-help at r-project.org Subject: Re: [R] symmetric matrix multiplication On

Hi, Currently the `gaussian' family's initialization code signals an error if any response data are zero or negative and a log link is used. Given that zero or negative response data are perfectly legitimate under the GLM fitted using `gaussian("log")', this seems a bit unsatisfactory. Might it be worth changing it? The current offending code from `gaussian' is:

x <- NA na.act <- na.action(na.exclude(x)) y <- rep(0,0) naresid(na.act,y) ... currently produces the result... numeric(0) ... whereas the documentation might lead you to expect NA The behaviour is caused by the line if (length(x) == 0L) return(x) in `stats:::naresid.exclude'. Removing this line results in the behaviour I'd expected in the above example (and in a

Hi, According to the help file for model.frame/get_all_vars, the following should produce the same output from both functions, but it doesn't... > dat <- list(X=matrix(1:15,5,3),z=26:30) > model.frame(~z+X,dat) z X.1 X.2 X.3 1 26 1 6 11 2 27 2 7 12 3 28 3 8 13 4 29 4 9 14 5 30 5 10 15 > get_all_vars(~z+X,dat) [1] z X <NA> <NA> <0

mgcv 1.5-0 is now on CRAN. Main changes are: * REML and ML smoothness selection are now available. * A Tweedie family has been added. * `gam.method' has been replaced (see arguments `method' and `optimizer' for `gam') For other changes see the changeLog. Simon -- > Simon Wood, Mathematical Sciences, University of Bath, Bath, BA2 7AY UK > +44 1225 386603

re: Cubic splines in package "mgcv" I don't have access to Gu (2002) but clearly the function R(x,z) defined on p126 of Simon Wood's book is piecewise quartic, not piecewise cubic. Like Kunio Takezawa (below) I was puzzled by the word "cubic" on p126. As Simon Wood writes, this basis is not actually used by mgcv when specifying bs="cr". Maybe the point is

mgcv 1.5-0 is now on CRAN. Main changes are: * REML and ML smoothness selection are now available. * A Tweedie family has been added. * `gam.method' has been replaced (see arguments `method' and `optimizer' for `gam') For other changes see the changeLog. Simon -- > Simon Wood, Mathematical Sciences, University of Bath, Bath, BA2 7AY UK > +44 1225 386603

The plots look reasonable to me. The plot of residuals against linear predictor always looks scary when many of the fitted values are very close to zero, so I tend to look at residuals against sqrt(fitted) in such cases. I don't think that the presence of the zero curve is a reason to reject the model --- it's easy to produce such plots by fitting a completely correct model to simulated

Dear sir,    How to do bilinear time series in R?Is there any functions or packages?  thank you! -----Sincerely yours Kuangnan Fang 方匡南 敬上 department of statistics ,Economics school,Xia men University. Fujian Province (361005) China Mobile Phone：15860721915 SKYPE: ruiqwy MSN Messenger: ruiqwy@hotmail.com QQ:39863401 --- 09年3月31日，周二, r-help-request@r-project.org

Hi Greg, For quasi families I've used extended quasi-likelihood (see Mccullagh and Nelder, Generalized Linear Models 2nd ed, section 9.6) in place of the likelihood/quasi-likelihood in the expression for the (RE)ML score. I hadn't realised that this was possible before the paper was published. best, Simon ps. sorry for slow reply, the original message slipped through my filter for

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of > Ted.Harding at nessie.mcc.ac.uk > Sent: Sunday, December 05, 2004 7:14 PM > To: r-help at stat.math.ethz.ch > Subject: Re: [R] What is the most useful way to detect > nonlinearity in lo > > > On 05-Dec-04 Peter Dalgaard wrote:

Hi, I finally managed to make it work (I just needed to have a X11 window open). Thank you very much for your help. Agnes -----Original Message----- From: Ted Harding [mailto:Ted.Harding at nessie.mcc.ac.uk] Sent: Friday, July 21, 2006 3:34 PM To: Paquet, Agnes Cc: r-help at stat.math.ethz.ch Subject: RE: [R] connection to X11 problem On 21-Jul-06 Paquet, Agnes wrote: > Dear List, >

Hi, Thank you for responding quickly and explaining the behavior. By adding "include.lowest=TRUE,right=FALSE" and manually including breaks that resolved the simple test case. Next I updated my more complex data set, which already had manually defined breaks, and that resolved my issues there too. I have now gone in and updated all my functions which use hist() so I

Thanks much Ted. I actually had just tried what you suggest here before you posted, and resolved the problem. Thanks also for the other tips. I wrote x = as.vector(c(1:12)) because I thought that the mode of x might be the problem, the error message pointing to .Random.seed notwithstanding. On a related note, I did a brief test a couple weeks back where I ran a million random samples of 3 from

Hi again! Following up my previous posting below (to which no response as yet), I have located a report which situates this type of question in a longitudinal modelling context. http://www4.stat.ncsu.edu/~dzhang2/paper/glm.ps Generalized Linear Models with Longitudinal Covariates Daowen Zhang & Xihong Lin (This work seems to originally date from around 1999). They consider an outcome Y,

Hi Folks, Has anyone got a compiled binary of the package 'plm' and/or of the package 'kinship' for Debian Etch? I'm asking because I'd like to install 'plm', but have failed because it depends on 'kinship', and 'kinship' refuses to compile on my Debian Etch. The underlying reason is the Debian refuses to allow me to install the development

The thread "R licensing query" currently running has raised the classic critcisms of using Excel for statistics. I was wondering: Has anyone applied the same or similar set of tests to OpenOffice "calc"? Or would the Executive Summary be: "Calc is just like Excel"? (Not that I'm a spreadsheet user, if I can avoid it; but I sometimes get asked about such