similar to: Penalised spline regression

Hey all, I'm using the gam() function inside the mgcv package to fit a penalised spline to some data. However, I don't quite understand what exactly the intercept it includes by default is / how to interpret it. Ideally I'd like to understand what the intercept is in terms of the B-Spline and/or truncated power series basis representation. Thanks!

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Yesterday i installed then new SP1 RC for Microsoft Vista Enterprise, Since then I cant connect to our samba server any more. Samba is configured as ad member, with winbind and idmap backend = rid. Has anyone the same Problem ? Mit freundlichen Gr??en Michael M?ssler uhb consulting AG Chiemseering 1 84427 St. Wolfgang Tel.: 08085/939-131 Fax.: 08085/939-222 Web:

Hi, I have been trying to fit an un-penalised gam in mgcv (in order to get more reliable p-values for hypothesis testing), but I am struggling to get the model to fit sucessfully when I add in a te() interaction. The model I am trying to fit is: gam(count~ s(x1, bs = "ts", k = 4, fx = TRUE) + s(x2, bs = "ts", k = 4, fx = TRUE) + te(x2, x3, bs =

Anyone using the penalised partial likelihood routines in survival5 should update their version. A bug has been fixed in the S package: in coxph() models with penalised likelihood and strata it was possible in some circumstances to get an infinite loop or perhaps an incorrect answer. The new version (2.3) is on cran.r-project.org and will percolate through CRAN in the next few days. -thomas

Anyone using the penalised partial likelihood routines in survival5 should update their version. A bug has been fixed in the S package: in coxph() models with penalised likelihood and strata it was possible in some circumstances to get an infinite loop or perhaps an incorrect answer. The new version (2.3) is on cran.r-project.org and will percolate through CRAN in the next few days. -thomas

** High Priority ** Hello R users My issue is both theorical and technical. I would like to run a penalised discriminant analysis with the fda() function, but I don''t know all the details of splines theory. I try on the example of the phonems from the article "Penalised Discriminant Analysis" of Hastie, Buja and Tibshirani 1994 : 5 groups and 256 variables. The 256

A nearly complete port of the new survival5 package has been sent to CRAN and will soon be appearing on a mirror near you in the contrib/devel area. This new package, the successor to survival4, has a more stable likelihood maximiser for parametric survival models and incorporates penalised likelihoods for adding smoothing splines, ridge regression, and (approximately) frailties to survival

I am confused on how the log-likelihood is calculated in a parametric survival problem with frailty. I see a contradiction in the frailty() help file vs. the source code of frailty.gamma(), frailty.gaussian() and frailty.t(). The function frailty.gaussian() appears to calculate the penalty as the negative log-density of independent Gaussian variables, as one would expect: >

On Tue, 6 May 2003, Jerome Asselin wrote: > > I am confused on how the log-likelihood is calculated in a parametric > survival problem with frailty. I see a contradiction in the frailty() help > file vs. the source code of frailty.gamma(), frailty.gaussian() and > frailty.t(). > > The function frailty.gaussian() appears to calculate the penalty as the > negative

hi I'm puzzled as to the relation between the REML score computed by gam and the formula (4) on p.4 here: http://opus.bath.ac.uk/22707/1/Wood_JRSSB_2011_73_1_3.pdf I'm ok with this for poisson, or for quasipoisson when phi=1. However, when phi differs from 1, I'm stuck. #simulate some data library(mgcv) set.seed(1) x1<-runif(500) x2<-rnorm(500)

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

I have a Windows server 2003 Domain controller with a share called DC02Data. I can connect to this share successfully from several RedHat boxes, running samba 2.2.7. However, on several other RedHat machines, running samba 3.0.9 I cannot connect properly. In fact, I actually seem able to establish a mount successfully, but cannot then view the files, as shown below: [root@ixapp01 mnt]#

Dear All, Thank you for the replies to my first thread here: http://r.789695.n4.nabble.com/global-optimisation-with-inequality-constraints-td3799258.html. So far the best result is achieved via a penalised objective function. This was suggested by someone on this list privately. I am still looking into some of the options mentioned in the original thread, but I have been advised that there may

With `obscure' I mean there is no appdb entry for it. The game (~?UhB?Y - Marisa to Alice -MariAri-) is a technically simple puzzle game, but it crashes during certain animations. `Worlds' (set of levels) show the animation only the first time you try so it is just annoyance, but boss levels always show that animation so you cannot play them. I am using wine 1.3.23; with a clean prefix

Hello All, I'm actually the system administrator of a UNIX system where several users use R version 2.6.0. I have a user who is trying to use the SURVEY package, and when he does, he gets the message: survey' is not a valid package -- installed < 2.0.0? When I run the library() command, I get (see below): Anything that is listed as ** No title available (pre-2.0.0 install?) **

SEE ALSO ORIGINAL POSTING IN PR#2933 On May 6, 2003 03:58 pm, Thomas Lumley wrote: > > Looking at a wider context in the code > > pfun <- function(coef, theta, ndeath) { > if (theta == 0) > list(recenter = 0, penalty = 0, flag = TRUE) > else { > recenter <- log(mean(exp(coef))) > coef <- coef - recenter

Hi All, I've found a few references in the mailing list and documentation to constrained least squares fitting, but little on restrained least squares. To clarify what I mean, a constraint might limit a parameter to a particular value (e.g. x=5.0, or exactly within the bounds 4.9 - 5.1), whereas a restraint adds some further information to the problem about the certainty of the starting point

Readers, Using version 251 I tried the following command: lm(y~a+b,data=datafile) Resulting in, inter alia: ... coefficients (intercept) a 1.2 3.4 Packages installed: acepack ace() and avas() for selecting regression transformations adlift An adaptive lifting scheme algorithm akima Interpolation of irregularly spaced

> Hello R-help, > > > We are running R version 2.6.0 (2007-10-03). I believe that I got it > from www.sunfreeware.com. A number of the packages that we attempt to > download from http://www.r-project.org/ give us the error message > below when we attempt to run them. > > Can anyone tell me what I need to do to gett these packages to run > properly? > >