similar to: terms.inner() reprise

Question: I am trying to impliment a function in R that we use quite regularly in Splus, and it fails due to a lack of the "terms.inner" function in R. The substitute is? Part question and part soapbox: Why remove terms.inner from R? It's little used, but rather innocuous. Mostly soapbox: I figured it was no big deal, as I originally discovered the use of terms.inner from

Hello, I am using the function step.gam() from the 'gam' package (header info from library(help=gam) included below) and have come across some behavior that I cannot understand. In short, I have written a function that 1) creates a dataframe, 2) calls gam() to create a gam object, then 3) calls step.gam() to run stepwise selection on the output from gam(). When I do this, gam()

I have contributed a "gam" library to CRAN, which implements "Generalized Additive Models". This implementation follows closely the description in the GAM chapter 7 of the "white" book "Statistical Models in S" (Chambers & Hastie (eds), 1992, Wadsworth), as well as the philosophy in "Generalized Additive Models" (Hastie & Tibshirani 1990,

I have contributed a "gam" library to CRAN, which implements "Generalized Additive Models". This implementation follows closely the description in the GAM chapter 7 of the "white" book "Statistical Models in S" (Chambers & Hastie (eds), 1992, Wadsworth), as well as the philosophy in "Generalized Additive Models" (Hastie & Tibshirani 1990,

This is covered in the helpfile, but perhaps not clearly enough. The gam chapter in the "white book" has more details. step.gam moves around the terms in the scope aregumnet in an ordered fashion. So if a scope element is ~ 1 + x +s(x,4) + s(x,8) and the formula at some stage is ~ x + .... then if direction="both", the routine checks both "1" and

I have posted an update to the GAM package. Note that this package implements gam() as described in the "White" S book (Statistical models in S). In particular, you can fit models with lo() terms (local regression) and/or s() terms (smoothing splines), mixed in, of course, with any terms appropriate for glms. A number of bugs in version 0.92 have been fixed; notably 1) some problems

I have posted an update to the GAM package. Note that this package implements gam() as described in the "White" S book (Statistical models in S). In particular, you can fit models with lo() terms (local regression) and/or s() terms (smoothing splines), mixed in, of course, with any terms appropriate for glms. A number of bugs in version 0.92 have been fixed; notably 1) some problems

Dear List, This may be related to this email thread initiated by Ben Bolker last month: https://stat.ethz.ch/pipermail/r-devel/2011-July/061630.html In answering this Question on StackOverflow http://stackoverflow.com/q/7195628/429846 I noticed that `methods()` was not listing some S3 methods for `plot()` provided by the mgcv package. At the time I wanted to check the development version of R as

Hi all, My question concerns 2 error messages; one in the gam package and one in the mgcv package (see below). I have read help files and Chambers and Hastie book but am failing to understand how I can solve this problem. Could you please tell me what I must adjust so that the command does not generate error message? I am trying to achieve model selection for a GAM which is required for

Dear R-users, I have 1 remark and 1 question on the inclusion of interactions in the gam function from the gam package. I need to fit quantitative predictors in interactions with factors. You can see an example of what I need in fig 9.13 p265 from Hastie and Tibshirani book (1990). It's clearly stated that in ?gam "Interactions with nonparametric smooth terms are not fully

Dear r-helpers, I use function step.gam (package gam, T. Hastie) with several explanatory variables to build a model. Unfortunately, I obviously have too many variables. This message occurs on my 4 core 64bit machine with 8GB RAM in R2.11.1 for Windows (64bit build): Error in array(FALSE, term.lengths) : 'dim' specifies too large an array I read that this message occurs when running out

Running R version 3.3.1 (2016-06-21) Bug in Your Hair I have discovered an issue with model.frame() with regard to its implementation of the na.action argument. This impacts the gam package. We are expecting the last thing to happen in model.frame() is that it runs na.action on the frame it has produced. In the example below, we use "na.action=na.omit", which calls for subsetting

Dear R-list members, Once a gam (package gam) model has been fitted with family=poisson, is there some R function that could extract the diagonal elements of the smoother matrix S, to be used in a cross-validation for the selection of the best smoothing parameter, following equation 3.19 on page 48 of the book T.J. Hastie and R.J. Tibshirani, Generalized Additive Models, Chapman and Hall/CRC,

I read the list in digest form which sometimes makes me late to respond. Peter Dalgaard wrote: In all fairness, it should probably be noted that quite a few people swear BY S4 in addition to those who swear AT it. Lest I give the impression of only dislike -- the coxme package (major rewrite nearly done, I'm now testing) depends heavily on the bdsmatrix package which implements a very

Hi, has somebody found a solution for the single smbd process opened on a samba server by TS 2008? Or found the correct syntax for multiuserenable on Windows 2008 server? Thanks, Emanuele

Hi, About a year and a half ago, Hank Leininger posted a plea to this list for the inclusion of an Include directive in OpenSSH's configuration file. Hank's suggestion is detailed and thorough enough IMHO, so instead of repeating it I'll link it here http://marc.info/?l=openssh-unix-dev&m=118236823907002&w=2 . I'm also interested in this feature, and though my C

Hi, I am fitting two models, a generalized linear model and a generalized additive model, to the same data. The R-Help tells that "A generalized additive model (GAM) is a generalized linear model (GLM) in which the linear predictor is given by a user specified sum of smooth functions of the covariates plus a conventional parametric component of the linear predictor." I am fitting the GAM

Last week I posted a question about monitoring Rails applications. Basically, the java folks at my business cited one of their reasons for sticking with Java is it''s monitoring tools. After picking some ears, I found out that the one we''re looking at most is JBoss Operations Network. And I have to say, it''s pretty neat.

hi, i'm using gam() function from package mgcv with default option (edf estimated by GCV). >G=gam(y ~ s(x0, k = 5) + s(x1) + s(x2, k = 3)) >SG=summary(G) Formula: y ~ +s(x0, k = 5) + s(x1) + s(x2, k = 3) Parametric coefficients: Estimate std. err. t ratio Pr(>|t|) (Intercept) 3.462e+07 1.965e+05 176.2 < 2.22e-16 Approximate significance of smooth

I have uploaded a new package to CRAN called ProDenICA. This fits ICA models directly via product-density estimation of the source densities. This package was promised on page 567 in the 2nd edition of our book 'Elements of Statistical Learning' (Hastie, Tibshirani and Friedman, 2009, Springer) . Apologies that it is so late. The method fits each source density by a tilted gaussian