similar to: lme model specification

*Dear R-help: My name is Rodrigo and I have a question with nlme package in R to fit a mixed beta regression model. The details of the model are: Suppose that:* *j in {1, ..., J}* *(level 1)* *i in {1, ..., n_j}* *(level 2)* *y_{ij} ~ Beta(mu_{ij} * phi_{ij}; (1 - mu_{ij}) * phi_{ij}) y_{ij} = mu_{ij} + w_{ij} * *with* *logit(mu_{ij}) = Beta_{0i} + Beta_{1i} * x1_{ij} + b2 * x2_{ij}

*Dear R-help: My name is Rodrigo and I have a question with nlme package in R to fit a mixed beta regression model. I'm so sorry. In the last email, I forgot to say that W is also a unknown parameter in the mixed beta regression model. In any case, here I send you the correct formulation. ** Suppose that:* *j in {1, ..., J}* *(level 1)* *i in {1, ..., n_j}* *(level 2)* *y_{ij} ~

Dear R-Users I have the following matrix > out$desc [,1] [,2] [1,] "" "" [2,] "y_{01}(k-001)" "" [3,] "y_{01}(k-002)" "" [4,] "y_{01}(k-003)" "" [5,] "u_{01}(k-001)" "" [6,] "u_{01}(k-002)" "" [7,] "u_{01}(k-003)" ""

Hi, P-values in Durbin-Watson test obtained through the use of functions available in packages "lmtest" and "car" are different. The difference is quite significant. function "dwtest" in "lmtest" is much faster than "burbinwatson" in "car". Actually, you can take a nap while the latter trying to calculated Durbin-Watson test. My question

Dear R users, I am trying to find a package that can estimate an autoregressive model for discrete data. I am imagining a Poisson or Gamma process in which the mean (say mu) follows a process such as mu_t = a + b*x + c*mu_{t-1} Suppose I have data on the time-series Poisson outcomes and x and would like to obtain ML estimates for b and c. Does anyone know of a package that can do this

Dear List: My question is more statistical than R oriented (although it originates from my work with nlme). I know statistical questions are occasionally posted, so I hope my question is relevant to the list as I cannot turn up a solution anywhere else. I will frame it in the context of an R related issue. To illustrate the problem, consider student achievement test score data with multiple

Can someone offer some advice on how to properly evaluate a SYMSXP from a .Call ? I have the following in R: variable xn, with an attribute "mu" which references the variable mu in the global environment. I know "references" is a loose term; mu was defined in this fashion as a way to implement deferred binding: foo <- function(x,mu) { attr(x,"mu") <-

I need to refresh my memory on Probability Theory, especially on conditional probability. In particular, I want to solve the following two problems. Can somebody point me some good books on Probability Theory? Thank you! 1. Z=X+Y, where X and Y are independent random variables and their distributions are known. Now, I want to compute E(X | Z = z). 2.Suppose that I have $I \times J$ random number

Hi, I am making some DNA distances and I would like to use dist.dna as matrix in R, but this command does not include models like GTR... Is there some command or alternative using dist.dna in ape package for models not included like GTR? I would appreciate any help given Thank you very much, Ignacio Quintero Laboratorio de biología evolutiva de vertebrados (Evolvert) Departamento de Ciencias

Dear R users, I'd like to compute X like below. X_{i,t} = 0.1*t + 2*X_{i,t-1} + W_{i,t} where W_{i,t} are from Uniform(0,2) and X_{i,0} = 1+5*W_{i,0} Of course, I can do this with "for" statement, but I don't think it's good idea because "i" and "t" are too big. So, my question is that Is there any better idea to avoid "for" statement

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hello, I have a simple question on the text() method in plots, e.g.: text(3,4,adj=1,cex=1.0, expression(alpha == beta)) I know there exists a lot more like frac(), etc which could be used for expression. But a help(frac) doesn't return any results - where do I have to look for a documentation of possible text commands? More in detail I'm

Dear R Help, I am trying to fit a nonlinear model for a mean function $\mu(Data_i, \beta)$ for a fixed covariance matrix where $\beta$ and $\mu$ are low- dimensional. More specifically, for fixed variance-covariance matrices $\Sigma_{z=0}$ and $\Sigma_{z=1}$ (according to a binary covariate $Z $), I am trying to minimize: $\sum_{i=1^n} (Y_i-\mu_(Data_i,\beta))' \Sigma_{z=z_i}^{-1} (Y_i-

Hi, I have a linear mixed-effects model object and want to extract the 95% confidence intervals for the fixed and random effects, respectively. I found the function intervals() for confidence intervals for the fixed effects but no corresponding function for the random effects. Does it exist or do I have to calculate the confidence intervals for the random effects myself? Greetings, joerg

Hello list. I'm trying to rebuild the 2.6.9.67.0.20.EL kernel, but it fails even without modifications. How did I try it? Created a (non-root) build environment (not a mock ) Installed the kernel.scr.rpm and did a rpmbuild -ba --target=`uname -m` kernel-2.6.spec 2> prep-err.log | tee prep-out.log The build failed at the end: Processing files: kernel-xenU-devel-2.6.9-67.0.20.EL Checking

Hi, I want to fit the following model to my data: Y_t= a+bY_(t-1)+cY_(t-2) + Z_t +Z_(t-1) + Z_(t-2) + X_t + M_t i.e. it is an ARMA(2,2) with some additional regressors X and M. [Z_t's are the white noise variables] How do I find the estimates of the coefficients in R? And also I would like to know what technique R employs to find the estimates? Any help is appreciated. Thanks,

hi lee. I see your problem with trunk iax, probably i don't have the solution but i don't knew if you can help me to solve mine. i want to connecte two asterisk server: server A and server B. i want make possible calls betwen all asterisk users.: users in server A with sip number 022100 can phone another sip user in server B with number 037100. this is my config:

sorry, I forgot my sessionInfo: please see below. -------- Original Message -------- Subject: puzzled with plotmath Date: Thu, 20 Jan 2011 12:48:18 +0100 From: Claudia Beleites <cbeleites at units.it> To: R Help <r-help at r-project.org> Dear all, I'm puzzled with matrix indices in plotmath. I'm plotting matrix elements: Z [i, i], and I'd like to put that as label.

Hello I would like to add .reg file to all samba clients (windows xp) in quiet mode. How can I do it ? It is possible from eg netlogon?? ---------------------------------------------------- ERROR! ... . .... bEZb??DnY prOgrAm__o nowo??iAcH w_ ?wiEcie G_iER na.jNowSzy_OdcinEk_ : co $Zykuj? tw?rcy caLL of Duty4, czym JeST The CLUB ............. poD??cz si?:

Hi all, I am trying to minimize the quardratic form w'Aw, with certain constraints. In particular, (1) A=(a_{ij}) is n by n matrix and it is symmetric positive definite, a_{ii}=1 for all i; and 0<a_{ij}<1 for i not equal j. (2) w'1=n; (3) w_{i}>=0 Analytically, for n=2, it is easy to come up with a result. For larger n, it seems difficult to obtain

Hi all, I want to fit the following model to my data: Y_t= a+bY_(t-1)+cY_(t-2) + Z_t +Z_(t-1) + Z_(t-2) + X_t + M_t i.e. it is an ARMA(2,2) with some additional regressors X and M. [Z_t's are the white noise variables] So, I run the following code: for (i in 1:rep) { index=sample(4,15,replace=T) final<-do.call(rbind,lapply(index,function(i)