similar to: Problem with mgcv PACKAGES file format?

Hello ... I found this due to a situation where installed.packages() was given a lib.loc argument that turned out to not have any R packages installed. As an example: > z <- tempfile() > dir.create(z) > installed.packages(z) Error in "colnames<-"(*tmp*, value = c("Package", "LibPath", pkgFlds)) : dimnames applied to non-array Looking at the code,

Good day to all of you and thank you for reading this. I certainly must have done something awfully wrong when I downloaded and installed R 2.0.0 on a PC with Windows 98. You will find below what happens when I try to 'update.packages()'. I know what the first 'warning message' means. About the others, I ain't got no clue. Thank you very handsomely for your wisdom. And

Hi All: I tried to update the package mgcv from my current version 1.1-8 to mgcv version 1.2. Using the command update.packages("mgcv") to update mgcv failed in my computer and the returning message was: "Error in old.packages(lib.loc=lib.loc, contriburl=contriburl, method=method, :no installed.packages for (?invalid) lib.loc=mgcv" When I typed installed.packages(), I got

Hi, I've been using gamm4 to build GAMMs for exploring environmental influences on genetic ancestry. Things have gone well and I have 2 very straightforward questions: 1. I've used method=REML. Am I correct that this is an alternative method for estimating the smooth functions in GAMMs rather than GCV that is often used for GAMs? I've read up on REML and it makes sense, but I'm

I am using gam in mgcv (1.3-22) and trying to use gcv to help with model selection. However, I'm a little confused by the process of assessing GCV scores based on their magnitude (or on relative changes in magnitude). Differences in GCV scores often seem "obvious" with my poisson gams but with negative binomial, the decision seems less clear. My data represent a similar pattern as

Hi, I need further help with my GAMs. Most models I test are very obviously non-linear. Yet, to be on the safe side, I report the significance of the smooth (default output of mgcv's summary.gam) and confirm it deviates significantly from linearity. I do the latter by fitting a second model where the same predictor is entered without the s(), and then use anova.gam to compare the

HI, i tried to install package by using update.packages( "locfit" ) I got the following error: trying URL `http://cran.r-project.org/src/contrib/PACKAGES' Content type `text/plain; charset=iso-8859-1' length 172492 bytes opened URL .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... ..........

Hello, After reinstalling the whole OS and R as well, I tried to update.packages() and get the follwing error message: concerning the mgcv update: atlas2-base is installed and blas as well (on debian). I haven't found lf77blas, I assume it's a library or something similar associated with blas. any suggestion how to solve that, thanks Martin * Installing *source* package

Hi I just upgraded my debian/stable to R 2.7.1 via apt-get install r-base r-base-core r-base-dev, and then began to update.packages() > update.packages(lib.loc="/usr/local/lib/R/site-library") > update.packages(lib.loc="/usr/lib/R/library") but I get: .... * Installing *source* package 'mgcv' ... ** libs gcc -std=gnu99 -I/usr/share/R/include -fpic -g

I use the ugly hack shown below as my .Rprofile (mainly because I couldn't find any other way to spawn a new mozilla window on starting R or calling help.start(), but then send all the help html documents to that new window). With a recent change from a cvs checkout to the released 1.9.0 I find that the new hs() appears if there is nothing of that name in .RData, but if there is the old hs()

Hello -- I am trying to compile R-2.9.2 on IBM Power5 machine with AIX 5.3. I have posted three previous posts. Over time I have made significant progress towards getting a successful build. I am now getting the following error: ========================================================== begin installing recommended package mgcv * Installing *source* package 'mgcv' ... ** libs gmake[2]:

Hi, I am fairly new to GAM and started using package mgcv. I like the fact that optimal smoothing is automatically used (i.e. df are not determined a priori but calculated by the gam procedure). But the mgcv manual warns that p-level for the smooth can be underestimated when df are estimated by the model. Most of the time my p-levels are so small that even doubling them would not result

hi Using a ts or tprs basis, I expected gcv to decrease when increasing the basis dimension, as I thought this would minimise gcv over a larger subspace. But gcv increased. Here's an example. thanks for any comments. greg #simulate some data set.seed(0) x1<-runif(500) x2<-rnorm(500) x3<-rpois(500,3) d<-runif(500) linp<--1+x1+0.5*x2+0.3*exp(-2*d)*sin(10*d)*x3

Dear all, I'm trying to fit a pure additive model of the following formula : fit <- gam(y~x1+te(x2, x3, bs="cr")) ,with the smoothing parameter estimation method "magic"(default). Regarding this, I have two questions : Question 1 : In some cases the value of "mgcv.conv$fully.converged" becomes "FALSE", which tells me that the method stopped with a

I received the following error when I attempted to update my packages: updating HTML package descriptions Warning messages: 1: DESCRIPTION file of package 'file28862' missing or broken in: packageDescription(p, lib = lib, fields = pkgFlds) 2: number of columns of result not a multiple of vector length (arg 2) in: rbind(retval, c(p, lib, desc)) 3: DESCRIPTION file of package

Dear community, I encountered a very disturbing phenomenon today: When I try to fit any gam() with mgcv R aborts. I could not find any post regarding this in google, which mades in even more strange. I am using the latest Ubuntu, latest R and latest mgcv everything up to date. The crash occured too with the last mgcv 1.7-11. This is the output from the R shell: <pre> R version 2.14.0

Hi,everyone, I am studying the generalized additive model and employ the package 'mgcv' developed by professor Wood. However,I can not understand the example listed in check.in function. For example, library(mgcv) set.seed(1) dat <- gamSim(1,n=400,scale=2) ## fit a GAM with quite low `k' b<-gam(y~s(x0,k=6)+s(x1,k=6)+s(x2,k=6)+s(x3,k=6),data=dat) plot(b,pages=1,residuals=TRUE)

I have 11 possible predictor variables and use them to model quite a few target variables. In search for a consistent manner and possibly non-manual manner to identify the significant predictor vars out of the eleven I thought the option "select=T" might do. Example: (here only 4 pedictors) first is vanilla with "select=F" >

Hi, I am using GAMs (package mgcv) to smooth event rates in a penalized regression setting and I was wondering if/how one can select the order of the derivative penalty. For my particular problem the order of the penalty (parameter "m" inside the "s" terms of the formula argument) appears to have a larger effect on the AIC/deviance of the estimated model than the

This is my first time running GAMs in R. My csv file has these column headings: "X" "Y" "Sound" "Atlantic" "Blacktip" "Bonnet" "Bull" "Finetooth" "Lemon" "Scalloped" "Sandbar" "Spinner" "Abundance" "Diversity"