similar to: Random effect model

Dear everyone I am a new user,would like to combine these code together by using a loop,each function has three value as Tr = 1 - 3,how can i combine together? logitTr1 <-logit[logit[,"Study"]&logit[,"Tr"]==1,] (number of row in each group (1-3) is difference but equal in colume) fnTr1 <- function (p) sum(

Hi R users: Is there a function to obtain the correlation within groups from this very simple lme model? > modeloMx1 Linear mixed-effects model fit by REML Data: barrag Log-restricted-likelihood: -70.92739 Fixed: fza_tension ~ 1 (Intercept) 90.86667 Random effects: Formula: ~1 | molde (Intercept) Residual StdDev: 2.610052 2.412176 Number of Observations: 30 Number

I was wondering why this loop doesn't work! for (i in 1:k) fnTr[i] <- function (p) 0.5* sum ( n*log(2*pi) - log(sd(i)^2) +(logitp(i)-p)^2/sd(i)^2 ) outTr[i]<- nlm (fnTr[i],p=c(10),hessian=TRUE) minimumTr[i] <- outTr[i]$minimum valueTr[i] <- outTr[i]$estimate list (minimumTr[i],valueTr[i]) Has anyone can help me? Thank you very much Hathaikan

I''m a physicist working on fusion energy and dabble in statistics only occasionally, so please excuse gaps in my statistical knowledge. I''d appreciate any help that a real statistics expert could provide. Most people in my field do only very simple statistics, and I am trying to extend some work on multivariate linear regression to account for significant between-group

I would like to fit the following model: logit(p_{ij}) = \mu + a_i + b_j where a_i ~ N(0, \sigma_a^2) , b_j ~ N(0, \sigma_b^2) and \sigma_a = \sigma_b. Is it possible to fit a model with such a constraint on the variance components in glmer? -- View this message in context: http://r.789695.n4.nabble.com/glmer-question-tp4351829p4351829.html Sent from the R help mailing list archive at

I can ask my question using and example from Chapter 1 of Pinheiro & Bates. > # 1.4 An Analysis of Covariance Model > > OrthoFem <- Orthodont[ Orthodont$Sex == "Female", ] > fm1OrthF <- + lme( distance ~ age, data = OrthoFem, random = ~ 1 | Subject ) > summary( fm1OrthF ) Linear mixed-effects model fit by REML Data: OrthoFem AIC BIC

Please pardon an extremely naive question. I see related earlier posts, but no responses which answer my particular question. In general, I'm very confused about how to do variance decomposition with random and mixed effects. Pointers to good tutorials or texts would be greatly appreciated. To give a specific example, page 193 of V&R, 3d Edition, illustrates using raov assuming pure

Greetings, 1) Is there a nice way of extracting the variance estimates from an lme fit? They don't seem to be part of the lme object. 2) In a series of simulations, I am finding that with ML fitting one of my random effect variances is sometimes being estimated as essentially zero with massive CI instead of the finite value it should have, whilst using REML I get the expected value. I guess

Dear friends, I used the B-spline (degree=1) method to fit the piecewise linear function and the results are listed below. m.glm<-glm(mark~x+poly(elevation,2)+bs(distance,degree=1,knots=c(16.13,24)) +bs(y,degree=1,knots=c(-0.4357,-0.3202 )),family=binomial(logit),data=point) summary(m.glm) Coefficients: Estimate Std.

Dear List: I have a question regarding an MDS procedure that I am accustomed to using. I have searched around the archives a bit and the help doc and still need a little assistance. The package isoMDS is what I need to perform the non-metric scaling, but I am working with similarity matrices, not dissimilarities. The question may end up being resolved simply. Here is a bit of substantive

Hi, as you can see in the topic, I am trying to fit a normal mixture distribution with the approach suggested by Hamilton (1991). Since I couldn't find any existing packages including the quasi-bayesian mle, I have to write my own function. Unfortunately, I have absolutely no experience in doing this. If you're not familiar with the QB-MLE, I attached the formula as pdf. The idea

HI, I would like to extract the variance components estimation in lme function like a.fit<-lme(distance~age, data=aaa, random=~day/subject) There should be three variances \sigma_day, \sigma_{day %in% subject } and \sigma_e. I can extract the \sigma_e using something like a.fit$var. However, I cannot manage to extract the first two variance components. I can only see the results in

Hi, i need to minimize a quadratic function with boundary condidtions and one equality condition. In order to do that i converted the equality constraint into 2 inequality constaints and passed everything cia constrOptim, as the manual said: everything included in the ... will be passed to Optim that will pass it back to fn in case it does not need it. My code is the following: mat <-

Suppose I know the value of cumulative bivariate standard normal distribution. How can I solve correlation between variables? Pekka --------------------------------- [[alternative HTML version deleted]]

library(XML) download.file('http://polya.umdnj.edu/polya_db2/gene.php?llid=109079&unigene=&submit=Submit','index.html') tables=readHTMLTable("index.html",error=function(...){}) tables readHTMLTable gives me the following errors. Could somebody let me know how to suppress them? Opening and ending tag mismatch: center and table htmlParseEntityRef: expecting

I've seen some questions regarding the output of multiple objects from a function, however the suggestions all end up suggesting the use of return(list(result1=result1, result2=result2 , result3=result3)). How can I return multiple objects that are 2 big to be added to a list? -- View this message in context:

Can someone help me out with this problem? Write an R program to draw 10,000 random samples using the Polya Urn Scheme where the initial contents of the urn is one white ball and one black ball. Accumulate the proportion of white balls after each draw into one vector. Upload your R script file. HINT: You can simulate sampling one ball from an urn with N balls of which w are white and N - w are

Hi, I'm using R-2.12 on a linux 64bit machine. When I run a chunk of code inside a foreach() %do% { ...} or %dopar% {...} (with doMC backend) I keep getting a segfault. Running the *same* code within lapply(something, function(x) ... ) doesn't result in any segfaults. I'll paste the output below, but I'm not sure it would be helpful. I'm more curious how to go about smoking

Hello, OpenSSH 2.5.1p1 running under AIX 4.3.3ML06. When I send a HUP signal to the parent sshd, that parent process dies, it's children get "adopted" by init, and the following message is put in the error log ... Mar 13 12:01:48 whippet sshd[31644]: Received SIGHUP; restarting. Mar 13 12:01:48 whippet sshd[31644]: RESTART FAILED: av[0]='sshd', error: No such file or

I am trying to setup vinum on a box using 4.8 RELENG_4 (as of about a week ago snapshot). This box was running 4.6 /w vinum on same hard drives for the last 4 months wonderfully... but since it is my current 'scratch/backup' box, I just reinstalled with -STABLE. # uname -a FreeBSD polya.axista.com 4.8-STABLE FreeBSD 4.8-STABLE #22: Tue Jun 24 17:01:07 EDT 2003