similar to: random effects in lme

Dear all, Suppose I have a linear mixed-effects model (from the package nlme) with nested random effects (see below); how would I present the results from the random effects part in a publication? Specifically, I?d like to know: (1) What is the total variance of the random effects at each level? (2) How can I test the significance of the variance components? (3) Is there something like an

Dear all, for my diploma thesis I have to import huge XML-Files into R for statistical processing - huge means a size about 33 MB. I'm using the XML-Package version 1.9 As far as reading the complete file into R via xmlTreeParse doesn't work or is too slow, I'm trying to use xmlEventParse but I got completely stuck. I have many different type of nodes + <configuration>

1. If your code actually runs, you should upgrade R, and quit using `_' for assignment... 8-) 2. You seem to have an extraneous `]' after the na.exclude. Could that be the problem? Andy > From: Christoph Scherber > > actually, the situation is much more complicated. I am producing > multiple graphs within a "for" loop. For some strange reason, the >

Hi all, I'm a PhD student at sydney uni and am trying to run a non linear mixed model program to obtain estimates of parameters describing dairy cow lactation curves. At present, I have been able to get the data to converge using the S plus (S plus 2000) nlme function. However, when I put the same data into R (R 1.9.0), add in the nlme package and run the code, it does not converge by the

Hi I'm sorry about the triviality of my problem. I have a vector (v) of three columns (logA, logB, id). I want to compute (and plot) the correlation between logA and logB for different thresholds of id (e.g. >30, etc). So I tried: for(i in 1:100){ points(cor(v$logA[v$id>i], v$logB[v$id>i], use="complete.obs"), i)) } (i created a plot object already) but it comes with

Is there an R-language interface to the R API C-language functions Rf_logspace_add() and Rf_logspace_sub()? I don't see one but I may not looking under the right name. Various packages have functions which do that same sort of thing (log(exp(x)+exp(y)) and log(exp(x)-exp(y)) without unnecessary floating point errors). They have names like matrixStats::logSumExp(lx, na.rm=FALSE, ...)

Dear developers Neither Math.Rd nor Log.Rd mention the branch cuts that appear for complex arguments. I think it's important to include such information. Please find following two context diffs for Log.Rd and Math.Rd. [The pedants amongst us will observe that both sqrt() and log() have a branch point at complex infinity, which is not mentioned in the patch. Comments anyone?] rksh

Dear R users, according the help(log), the function log2(x) should give the natural logarithm of x. I expect in case of x=2 to to get 0.6931, however, R gives me 1 as a result. Similar, logb(2,2) gives 1 again. I'm wondering if I have missed something ? Yours Frank -- Frank Mattes, MD e-mail: f.mattes at ucl.ac.uk Department of Virology fax 0044(0)207 8302854 Royal Free Hospital

Survfit had a bug in some prior releases due to the use of both unique(times) and table(times); I fixed it by rounding to 15 digits per the manual page for as.character. Yes, I should ferret out all the usages instead, but this was fast and it cured the user's problem. The bug is back! A data set from a local colleage triggers it. I can send the rda file to anyone who wishes. The

Dear All, According to the Sturges rule, the number of classes of a histogram is the closest integer to 1 + logb(n,base=2) where n is the number of observations. The function hist(), by default, uses the Sturges rule. However, the code x <- 1:200 hist(x) produces a histogram with 10 classes and not 9 classes as determined by the Sturges rule. What am I missing? Thanks in advance, Paul

[ Not sure why, but the first time I sent this it never seemed to go through; apologies if you're seeing this twice ... ] I have some fully functional code that I'm guessing can be done better/quicker with some savvy R vector tricks; any help to make this run a bit faster would be greatly appreciated; I'm particularly stuck on how to calculate using "row-wise" vectors

What is wrong in the following nested if-else statements: if (Condition_1) { # begin IF_1 statement_1 statement_2 statement_3 if (Condition_2) { # begin IF_2 a<- a +1 } # end IF_2 statement_4 statement_5 statement_6 statement_7 if (Condition_3) {

Dear R-users, I am using R 2.13.0 and rms 3.3-0 , but can not reproduce figure 7.8 of the handouts *Regression Modeling Strategies* ( http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/course2.pdf) by the following code. Could any one help me figure out how to solve this? setwd('C:/Rharrell') require(rms) load('data/counties.sav') older <- counties$age6574 + counties$age75

I have a MLE task that for a small number of parameters finishes in a reasonable amount of time, but for my "real" case (with 17 parameters to be estimated) either takes far too long (over a day), or fails with "computationally singular" errors. So a) are there any parallel implementations of optim() (in R or otherwise) and b) how can I make my function more robust?

x <- rnorm(1e6); y <- log(x); # or logb(x) or log1p(x) w <- warnings(); print(object.size(w)); ## [1] 480 str(w); $ NaNs produced: language log(x) - attr(*, "dots")= list() - attr(*, "class")= chr "warnings" y <- log2(x); # or log10(x) w <- warnings(); print(object.size(w)); ## [1] 8000536 str(w); ## List of 1 ## $ NaNs produced: language

Hello, I am trying to cross-compile libc++ from my x86_64 linux system to armv7hf. We have our own gcc compiler that we build with crosstools-ng (based on gcc 6.3.0) and I set my environment like this: CC=armv7a-plex-linux-gnueabihf-gcc CXX=armv7a-plex-linux-gnueabihf-g++ CFLAGS=-fPIC -DPIC -mfloat-abi=hard -march=armv7-a -Os -mfpu=vfpv3-d16 --sysroot=<path> CXXFLAGS=-fPIC -DPIC

Hi all, given this example #start a<-c(0,70,50,100,70,650,1300,6900,1780,4930,1120,700,190,940, 760,100,300,36270,5610,249680,1760,4040,164890,17230,75140,1870,22380,5890,2430) length(a) b<-c(0,0,10,30,50,440,1000,140,70,90,60,60,20,90,180,30,90, 3220,490,20790,290,740,5350,940,3910,0,640,850,260) length(b) out<-ks.test(log10(a+1),log10(b+1)) # max distance D

At first glance, it looks like long double functions (such as fabsl and friends) are missing from your sysroot's <math.h>. Does your target support long double at all? -Dimitry > On 6 Feb 2018, at 09:51, Tobias Hieta via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > Hello, > > I am trying to cross-compile libc++ from my x86_64 linux system to armv7hf. We have

Hello Dimitry and thanks for your answer. I am pretty sure it does indeed support long double. It's configured with vfpv3-d16 - but I noticed that c++config.h in gcc has _GLIBCXX__HAS_FABSL and friends are undefined. I think I need to look deeper at the configuration of our toolchain. long double support is required in libc++ then I gather? -- Tobias On Tue, Feb 6, 2018 at 11:47 AM,

Is there any way to know how the "dmvt" function computes the hypergeometric function needed in the calculation for the density of multivariate t distribution? -- View this message in context: http://r.789695.n4.nabble.com/hypergeometric-function-in-mvtnorm-tp4483730p4483730.html Sent from the R help mailing list archive at Nabble.com.