similar to: Problem with simple random slope in gam and bam (mgcv package)

Dear useRs, I have used using the excellent mgcv package (version 1.7-12) to create a generalized additive model (gam) including random effects - represented with s(...,bs="re") - on the basis of dialect data. My model contains two random-effect factors (Word and Key - the latter representing a speaker) and I have added both random intercepts and various random slopes for these

Dear useRs, I am using mgcv version 1.7-16. When I create a model with a few non-linear terms and a random intercept for (in my case) country using s(Country,bs="re"), the representative line in my model (i.e. approximate significance of smooth terms) for the random intercept reads: edf Ref.df F p-value s(Country) 36.127 58.551 0.644

Dear useRs, I reran an analysis with bam (mgcv, version 1.7-17) originally conducted using an older version of bam (mgcv, version 1.7-11) and this resulted in the same estimates, but much lower standard errors (in some cases 20 times as low) and lower p-values. This obviously results in a larger set of significant predictors. Is this result expected given the improvements in the new version? Or

Hello, I'm trying to use the bam() function in the R mgcv package for a large set of grouped binary data. However, I have found that this function does not take data in the format of cbind(numerator, denominator) on the left hand side of the formula. As an example, consider the following dat1 <- data.frame(id=rep(1:6, each=3), num=rbinom(18, size=10, prob=0.8), den=rbinom(18, size=5,

Hi R users, I'm using the 'bam' function in mgcv to examine trends in a remotely sensed vegetation index. I have one random effect variable, 'cons' (with six levels) which identifies different subjects within this analysis. My model is specified as follows: rm4<-bam(trend~factor(zone)+s(cons,bs="re")+s(year,

Dear all, I am trying to use 'bam' to run the following generalized additive model: ### m <- bam(result ~ factor(city) + factor(year) + lnpopulation + s(lnincome_pc) + ,data=full_df,na.action=na.omit,family=ziP(theta = NULL, link = "identity",b=0)) But getting the following error: ### Error in bam(result : extended families not supported by bam The documentation for

Do you have the mgcv package installed (I think it's part of the standard distro, though) /loaded? ziP is there, not in BAM. Other than that, sorry, no clue. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Mon, Nov 6,

Hello everyone. I am doing a logistic gam (package mgcv) on a pretty large dataframe (130.000 cases with 100 variables). Because of that, the gam is fitted on a random subset of 10000. Now when I want to predict the values for the rest of the data, I get the following error: > gam.basis_alleakti.1.pr=predict(gam.basis_alleakti.1, +

Hello, I am trying to update the mgcv package on my Linux box and I keep getting an "Out of memory!" error. Does anyone know of a fix for this? Below is a snippet of the message that I keep getting: Thank you. Geoff ** R ** inst ** preparing package for lazy loading ** help *** installing help indices >>> Building/Updating help pages for package 'mgcv' Formats:

Hello R users, I have a quick question I was hoping to get your input on. I am new to R and the smooth statistical regression world, and am trying to wrap my mind around the issues concerning using splines for mixed effect modeling. My question is the following: in the ?gamm? function, generalized additive mixed models can be estimated by including random components. These can be explicitly

Dear R-help list, I?m using the mgcv package to plot predictions based on the gam function. I predict the chance of being a (frequent) participant at theater plays vs. not being a participant by age. Because my outcome variable is dichotomous, I use the binomial family with logit link function. Dataset in attachment, code to read it in R: data <- read.spss("pas_r.sav") attach(data)

Dear all; I'm kind of confused with the results obtained using the ginv function from package MASS and pinv function from Matlab. Accroding to the documentation both functions performs a Moore-Penrose generalized inverse of a matrix X. The problem is when I change the tolerance value, say to 1E-3. Here is some output from ginv 195.2674402 235.6758714 335.0830253 8.977515484 -291.7798965

mgcv: Constructing probabilities for binomial GAM with crossed random intercepts and factor by variable Hello, (I'm sorry if this has been discussed elsewhere; I may not have been looking in the right places.) I ran a binomial GAM in which "Correct" is modelled in terms of the participant's age and the modality in which the stimulus is presented (written vs spoken).

Dear useRs, I have a question with respect to fitting a non-linearity using gam (mgcv package, version 1.7-16). In a study I'm currently conducting, I'd like to find out if there is a breakpoint after which the effect of Age of Acquisition (AOA) of the second language changes. I.e. if the slope of AOA before the breakpoint (at a certain AOA) is different from the slope past the

Hi all: I've got a data of ".bam" which is created from my partner under linux sysyem. My system is window xp, and I wanna know how to read the .bam file. Many thanks! My best [[alternative HTML version deleted]]

Hi, I also had some problems using chan_oh323 together with gnugk. * <-> gnugk <-> h323-phone When I called the phone and hang up, befor the phone was picked up, the h323-phone continued ringing. The same, when the h323- and some sip-phones were called, and the sip-phone picked up the call first. (It is annoying, when you are talking to someone at the phone and the phone on the

Dear R-helpers, I'd like to understand how to test the statistical significance of a random effect in gamm. I am using gamm because I want to test a model with an AR(1) error structure, and it is my understanding neither gam nor gamm4 will do the latter. The data set includes nine short interrupted time series (single case designs in education, sometimes called N-of-1 trials in medicine)

Dear Ben, you answerd to Nancy Shackelford about Clarks 2Dt function. Since the thread ended just after your reply, I would like to ask, if you have an idea how to use this function in R I defined it the following way: function(x , p, u) { (p/(pi*u))*(1+(x^2/u))^(p+1) } and would like to fit this one to my obeservational data (count) [,1] [,2] [1,] 15 12 [2,] 45 13 [3,]

Dear friends, I have install the last version 2.10 and now I have probles with 'mgcv' which can be load. I proved to eliminated and reinstalled but always obtain the same message: > library (mgcv) This is mgcv 1.6-1. For overview type `help("mgcv-package")'. Error in runif(1) : .Random.seed is not an integer vector but of type 'list' Error : .onAttach non

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