similar to: Inconsistent linear model calculations

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?) **

When I type library() to see what is installed the following list in RED comes up. Packages in library '/home/jason/R/i686-pc-linux-gnu-library/2.13': abind Combine multi-dimensional arrays aplpack Another Plot PACKage: stem.leaf, bagplot, faces, spin3R, and some slider functions biglm bounded memory linear and

Dear R-helpers, I hope someone can help me with the following problem: I derived a variable from many others and produced data.frame: toktempo When I look at the variable name I get: names(toktempo) [1] "otok.V5" But I want the variable name to be Tempo so I googled around to find info about renaming variables. I found a webpage which seemed to indicate to me that there was a

> 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? > >

I just successfully compiled R-1.6.0 on a Red Hat 7.2 machine. When I tried to install "grid" from source, I got this error. Any suggestions? I don't think it is a dependency problem. I also attach the output from library(). Yuelin Li. ------------- > install.packages("grid") trying URL `http://cran.r-project.org/src/contrib/PACKAGES' Content type

Hallo, I just installed all needed packages for my project on my PC. But I cannot load all at one time. I now want to load limma. How can I realize the following plan: I want to install for example limma inclusive all needed other sub packages (add-on). Can anyone tell me the corresponding command? Thanks, Corinna Here is the result of the command library(): Pakete in Library

Dear List, While trying to define a customised CITATION file for a package, following R-exts, I realised that if I use only one 'citEntry' I got both a text description and a BibTex entry for the package, as for the 'nlme' package: -------------------------- citation('nlme') To cite package 'nlme' in publications use: Jose Pinheiro, Douglas Bates, Saikat

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

Hello All, I'm getting this error (Version: 1.9.0-1 on a debian system) > update.packages("mgcv") trying URL `ftp://mirror.aarnet.edu.au/pub/cran/src/contrib/PACKAGES' ftp data connection made, file length 169516 bytes opened URL .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... ..........

Hi all, I am trying to do an inversion of electromagnetic data with non-negative least squares method (Tikhonov regularisation) and have got it programmed in S-Plus. However I am trying to move all my scripts from S-Plus to R. Is there an equivalent to nnls.fit in R? I think this can be done with pcls? Right? S-Plus script: A, L and data are matrices, lambda is a vector of possible lambda

Hi R-users I am trying to use the GAM function of the mgcv package. But I am having problem trying to specify the k parameter. Although I managed to run some models by giving to the parameter some (random) value, and it is explained by Wood (2006) that it does not seem to "really" affect the final result, I would like to grasp better its meaning. I understand that is the

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 I would like to fit a non-linear regression to the follwoing data: quantiles<-c(seq(.05,.95,0.05)) slopes<-c( 0.000000e+00, 1.622074e-04 , 3.103918e-03 , 2.169135e-03 , 9.585523e-04 ,1.412327e-03 , 4.288103e-05, -1.351171e-04 , 2.885810e-04 ,-4.574773e-04 , -2.368968e-03, -3.104634e-03, -5.833970e-03, -6.011945e-03, -7.737697e-03 , -8.203058e-03, -7.809603e-03, -6.623985e-03,

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)

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

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,

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

Hello. I'm trying to analyze data, which is looking at the relationship between temperature and survival for fish (from fertilization to emergence). Looking at the raw data, there appears to be a bell shaped relationship. Ordinarily for survival data, I would run a generalized linear model (because the data has a binomial error structure). However, I am thinking that running a generalized

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