search for: bvars

Hello, I am looking for a way to obtain standard errors for emprirical Bayes estimates of a model fitted with lmer (like the ones plotted on page 14 of the document available at http://www.eric.ed.gov/ERICDocs/data/ericdocs2/content_storage_01/0000000b/80/2b/b3/94.pdf). Harold Doran mentioned (http://tolstoy.newcastle.edu.au/~rking/R/help/05/08/10638.html) that the posterior modes' variances

Hi all, To follow up on an older thread, it was suggested that the following would produce confidence intervals for the estimated BLUPs from a linear mixed effect model: OrthoFem<-Orthodont[Orthodont$Sex=="Female",] fm1OrthF. <- lmer(distance~age+(age|Subject), data=OrthoFem) fm1.s <- coef(fm1OrthF.)$Subject fm1.s.var <- fm1OrthF. at bVar$Subject fm1.s0.s <-

...er of variables increases. Is there a way I can do this kind of processing using a loop? I tried defining a vector to hold the names for the "c variables" (e.g. c1,c2, ... cn) and creating new variables in a loop using code like: avars<-c("a1","a2","a3") bvars<-c("b1","b2","b3") cvars<-c("c1","c2","c3") for(i in 1:3){ df$cvars[i]<-df$avars[i]/df$bvars[i] } But the variable references don't resolve properly with this particular syntax. Any help would be much appreciated. Chee...

Dear All, With kind help from several friends on the list, I am getting close. Now here are something interesting I just realized: for random effects, lmer reports standard deviation instead of standard error! Is there a hidden option that tells lmer to report standard error of random effects, like most other multilevel or mixed modeling software, so that we can say something like "randome

Using lmer in the lme4 package, you can compute the conditional variance-covariance matrix of the random effects using the bVar slot: bVar: A list of the diagonal inner blocks (upper triangles only) of the positive-definite matrices on the diagonal of the inverse of ZtZ+Omega. With the appropriate scale factor (and conversion to a symmetric matrix) these are the conditional variance-covariance

I want to compute confidence intervals for the random effect estimates for each subject. From checking on postings, this is what I cobbled together using Orthodont data.frame as an example. There was some discussion of how to properly access lmer slots and bVar, but I'm not sure I understood. Is the approach shown below correct? Rick B. # Orthodont is from nlme (can't have both nlme and

...in Pinheiro and Bates (2000) > Mixed-Effects Models in S and S-Plus (Springer). The may be more > accurate procedures available in the literature, but none so simple as > this as far as I know. > > Comments? > spencer graves > p.s. It looks like fm at bVars is a list containing vectors of length 29 > and 6 in your example. I don't know what they are, but I don't see > how they can be standard errors in the usual sense. > > Doran, Harold wrote: > > > These are the posterior variances of the random effects (I think &g...

I have not been able to find any programs for running vector autoregressions with R. I am interested in running Bayesian VARs and also running VARs that run all combinations of variables in the vector. Is anyone currently developing this? -Nirav Mehta

I mad the change, and still have the problem. I investigate more the source code of llvm. First, I change isRawBitcode function to print the content of the parameter like this: original: http://llvm.org/docs/doxygen/html/ReaderWriter_8h_source.html#l00081 inline bool isRawBitcode(const unsigned char *BufPtr, const unsigned char *BufEnd) { // These bytes sort

all of: ---- // cout << "lsr: " << lsr << "\n"; llvm::MemoryBuffer* mbjit = llvm::MemoryBuffer::getMemBufferCopy (sr); ------ string lsr = sr.str(); // cout << "lsr: " << lsr << "\n";

This segfault occuring only under valgrind, in shell way, and in gdb way i have Invalid bitcode signature simple_scev_dynamic_array: /home/willy/apollo/llvm/include/llvm/Support/ErrorOr.h:258: storage_type *llvm::ErrorOr<llvm::Module *>::getStorage() [T = llvm::Module *]: Assertion `!HasError && "Cannot get value when an error exists!"' failed. Command terminated by

Hello, I having a weird problem while writing a bytecode module to a string, and after read/parse it for unsing on a jit. I write a pass to export function to module, and put this module inside a global variable. I use WriteBitcodeToFile for this. For debuging, after this write, I try to load the exported module with parseBitcodeFile. This two step works. After, while the compiled program is

Hello Willy, Here is the dump from one of my bitcode files: 0000000 42 43 c0 de 21 0c 00 00 25 05 00 00 0b 82 20 00 As expected, 0x42 (= B), 0x43 (= C), xc0 and 0xde are in correct order. In your case, the first byte is read as 37 (= 0x25). I wonder why? When you check the bytes yourself, you get expected results. When the same bytes are read from Stream object, you get a different result (maybe

attempting to do multivariate modelling in R with known future conditions (in this case variable 'b') using MSBVAR and hc.forecast. The sample code (a paired down representation) does not give anywhere near the expected results - I am assuming that a forecast 8 steps out would approximate 'a' as the sequence 1.1,2.1,3.1,100.1 corresponding to the input set. I have varied the input

Hi all, I have the following code, When I run the code, it never terminate this is because of the while loop i am using. In general, if you need a loop for which you don't know in advance how many iterations there will be, you can use the `while' statement so here too i don't know the number how many iterations are there. So Can some one suggest me whats going on? I am using the

I can't find a way to retrieve z values and p-values from the output from lmer in the lme4 package. How is this done? Rick B.

Hi all, I got another VAR question here and really appreciate if somebody would help me out :) I have five time series, say A,B,C,D,E. My objective is to predict the series A using the rest, that is, B, C, D and E. A Vector Autoregression Model should work here. But first of all, I should select which series of B, C, D and E to be include in the VAR model, as well as the number of lags. I wonder

Hi, I have been having a tedious issue with lmer models with lots of factors and lots of levels. In order to get the basic information at the beginning of the print out I also have to generate these enormous tables as well. Is there a method command to leave off all of the effects and correlations? Or, do I have to go to string commands?

Hello All, I would like to retrieve some of the results from the lmer(...) function in library lme4. If I run a model, say fm.1 <- lmer(y ~ 1 + (1 | x), data = dog) and try names(fm.1), I get NULL. Is there anyway to retrieve the information? Thanks

Hi, I would like to know whether it is possible to obtain a value of significance for random effects when aplying the lme or related functions. The default output in R is just a variance and standard deviation measurement. I feel it would be possible to obtain the significance of these random effects by comparing models with and without these effects. However, I'm not used to perform