similar to: pdIdent in smoothing regression model

Is there a way to specify a Z matrix using the lmer function, where the model is written as y = X*Beta + Z*u + e? I am trying to reproduce smoothing methods illustrated in the paper "Smoothing with Mixed Model Software" my Long Ngo and M.P. Wand. published in the /Journal of Statistical Software/ in 2004 using the lme4 and Matrix packages. The code and data sets used can be found at

Dear All, I revise my question about the problem I have. Take a look at the article http://www.jstatsoft.org/v09/i01 and download the attached code. try to run one of the codes for example section 2.1 in R here is the code fossil <- read.table("fossil.dat",header=T) x <- fossil$age y <- 100000*fossil$strontium.ratio knots <- seq(94,121,length=25) n <- length(x) X <-

I'm trying to do some smoothing with lme and am having some difficulty bringing commands over from S-PLUS to R. I have the following setup (modified from Ngo and Wand, 2004): set.seed(1) x <- runif(200) y <- sin(3*pi*x) + rnorm(200)*.4 ## library(splines) z <- ns(x, 4) The following runs without error on S-PLUS f <- lme(y ~ 1, random = pdIdent(~ -1 + z)) But in R I get

I was wondering if one can have the coefficients of VAR model sorted according to variable names rather than lags. If you notice below, the output is sorted according to lags. >VAR(cbind(fossil,labour),p=2,type="const") VAR Estimation Results: ======================= Estimated coefficients for equation fossil: =========================================== Call: fossil = fossil.l1

Dear R-list, I?m trying to use the lmer of the lme4 package to fit a linear mixed model of the form Y = Xb + Zu + e and I can?t figure out how to control the covariance structure of u. I want u ~ N(0,sigma^2*I). More precisely I?m trying to smooth a curve through data using the "Penalized Splines as BLUPs" method as described in Ruppert, Wand & Carroll (2003). So I have Z = [Z1

Dear all, I am trying to fit a model with crossed random effects using lme. In this experiment, I have been measuring oxygen consumption (mlmin) in bird nestlings, originating from three different treatments (treat), in a respirometer with 7 different channels (ch). I have also measured body mass (mass) for these birds. id nest treat year mlmin mass ch hack 1EP51711 17

Greetings, I might have missed something in the list here.. But could someone point out some introductory material / docs regarding cmirror? Is there something (even beta would do) in CentOS to read and understand about this? OT- On Fossils: While I cannot claim "Fossil state" anywhere near some of the people who were doing cards -- I knew about them though -- when I was born, I have

Hello all, In lme4 if you want to model two non-nested random effects you code it like this: mod1 <- lmer(y~x + (1|randomvar1) + (1|randomvar2)) How would you go about to model something similar in nlme? In my database I have two variables for which I have repeated measures, lets call them "individual" and "year". But none of the "individuals" were measured in

Good Day, Included below is some code to generate data and to fit a mixed effects model to this fake data. The code works as expected when I call the function "lme" in Splus but not in R. The error message from calling lme in R is: "Error in getGroups.data.frame(dataMix, groups) : Invalid formula for groups" I installed the nlme package for R around 20 August

Dear All, I have a problem running this program on R. Z is a matrix of spline which is random > fit<-lme(anc~X,random=pdIdent(~Z)) Error in getGroups.data.frame(dataMix, groups) : Invalid formula for groups What I have done wrong?

On Jun 6, 2018, at 4:06 AM, Alice Wonder <alice at domblogger.net> wrote: > > I'm not anti-microsoft but I'm worried they will make changes that I don't like (e.g. requiring ms account, changing billing, etc.) so I figured better take control now. What had you using GitHub in the first place, then? Is it just the web UI, since you?ve apparently decided that none of

Dear maintainers and R-devel, Several orphaned CRAN packages are about to be archived due to outstanding QC problems, but have CRAN and BioC packages depending on them which would be broken by the archival (and hence need archiving alongside). Therefore we are looking for new maintainers taking over maintainership for one or more of the following packages: R2HTML SemiPar cghseg hexbin lgtdl

Hello- I'm new to R, coding and stats. (Oh no.) Anyway, I have about 12000 data points in a data.frame (dealing with dimensions and geological stage information for fossil protists) and have plotted them in a basic scatter plot. I also added a boxplot to overlay these points. Each worked fine independently, but when I attempt to superimpose them with add=true, I get a different scale for

Hi all, Does anyone know how to report heteroskedasticity and autocorrelation-consistent standard errors when using the "spm" command in SemiPar package? Suppose the original command is sp1<-spm(y~x1+x2+f(x3), random=~1,group=id) Any suggestion would be greatly appreciated. Thanks, Susan [[alternative HTML version deleted]]

Hello, Set up a CentOS 7.5 VM linode for git now that github has been bought. I'm not anti-microsoft but I'm worried they will make changes that I don't like (e.g. requiring ms account, changing billing, etc.) so I figured better take control now. Currently moving my private repos and have them set up in my home directory there, but my public repos - I want to set them up with a

I have been using lme from nlme to do a 3-way anova with all the effects treated as random. I was wondering if someone could direct me to an example of how to do this using lmer from lme4. I have 3 main effects, tim, trt, ctr, and all the interaction effects tim*trt*ctr. The response variable is ge. Here is my lme code: dat <-

Hi, I am using coxph in simulations and I want to store the "robust se" (or "se2" in frailty models) for each replicate. Is there a function to retrieve it, like vcov() for the variance estimate? Thanks! Lei Liu Assistant Professor Division of Biostatistics and Epidemiology Dept. of Public Health Sciences School of Medicine University of Virginia 3181 Hospital West

Dear R users, I'm trying to specify a generalized linear mixed model in R, basically a Poisson model to describe monthly series of counts in different regions. My aim is to fit subject-specific curves, modelling a non-linear trend for each region through random effects for linear splines components (see Durban et al, Stat Med 2005, or " Semiparametric regression" by Ruppert et al,

I've posted the following to R-help on May 15. It has reproducible R code for real data -- and a real (academic, i.e unpaid) consultion background. I'd be glad for some insight here, mainly not for myself. In the mean time, we've learned that it is to be expected for anova(*, "marginal") to be contrast dependent, but still are glad for advice if you have experience. Thank

Dear Sir / Madam I had been using Glusterfs of both nodes, and it is under in distribute mode. But I cannot use all of the gluster commands at one of the node recently, any gluster command not respond (E.g volume info or pool list), and I got the error in cli.log . Does anyone can help me, many thanks. Here is the log error: [cli.c:759:main] 0-cli: Started running gluster with version