similar to: scoping rules; summary

Hi I recently found a bug that was isomorphic to the following: ll1 <- 2 increment <- function(x) { l11 <- 1 return(x+ll1) #bug here } Of course, R is obeying the scoping rules just fine, but I'm evidently not setting the do.what.I.mean.not.what.I.say variable correctly. Now, how do I avoid making this type of error? ... and what is the best tool for tracking it down? --

Hello everybody, i already searched the archieves, but i still don't know what is wrong in my implementation, mybe anybody coud give me some advice ll1<-function(rho,theta,beta1,beta2,beta3,beta4,t,Szenariosw5,Testfaellew5,X1,X2) { n<-length(t) t<-cumsum(t) tn<-t[length(t)] Szenn<-Szenariosw5[length(Szenariosw5)]

Hello, I am new to R and I am trying to estimate a discrete model with three choices. I am stuck at a point and cannot find a solution. I have probability functions for occurrence of these choices, and then I build the likelihood functions associated to these choices and finally I build the general log-likelihood function. There are four parameters in the model, three of them are associated to

Hi all, I want to construct relatedness among individuals and have a look at the following script. ######################### rm(list=ls()) N=5 id = c(1:N) dad = c(0,0,0,3,3) mom = c(0,0,2,1,1) sex = c(2,2,1,2,2) # 1= M and 2=F A=diag(nrow = N) for(i in 1:N) { for(j in i:N) { ss = dad[j] dd = mom[j] sx = sex[j] if( ss > 0

This is just an idea for comment. Perl6, the upcoming version of Perl has separated out the runtime into a virtual machine called Parrot. There are already several small languages (one is C-like, one is Java-like and one is BASIC-like) that target Parrot and given the popularity of Perl its likely that others may attempt to target it too. If R could interface easily with Parrot then it might be

Hello, Is it possible to include information about phylogenetic relatedness among species (when species are replicates for each study within a meta-analysis) in a meta-anlaysis in the metafor package? Alternatively, I wonder if the method f Lajeunesse 2009 American Naturalist has been adopted in R in any fashion? Thanks, Scott Chamberlain [[alternative HTML version deleted]]

Dear R-list, maybe someone can help me with the following mixed-effects models problem, as I am unable to figure it out with the 'nlme-bible'. I would like to fit (in R, obviously) a so-called animal model (google e. g. "Heritability and genetic constraints of life-history" by Pettay et al.) to estimate the variance component that is due to genetic effects. The covariances of

Hi all, I previously emailed about a multinomial model, and after seeking some additional help, realized that since my response/outcome variables are not mutually exclusive, I need to use a multi-response model that is *not* multinomial. I'm now trying to figure out how to specify the priors on the multi-response model. Any help would be much appreciated. My data look like this: X

Dear list, I try to set a secondary y-axis in a lattice xyplot. This works. However, I am unable to set a proper legend/key together with the 2nd y-axis under general xyplot procedures. See example below. The combination of the par.settings with simpleTheme and other settings seems to go wrong. I couldn't find a solution from previous topics. Any suggestions? thanks in advance! Robbert

On Mon, Mar 10, 2014 at 3:59 PM, Olly Betts <olly at survex.com> wrote: > Exactly what approach the project takes isn't nailed down - it just > seemed something which would be interesting for a student to work on, > and would be useful to Xapian users. > > My understanding of the current clustering branch (which may not be > completely accurate) is that it clusters

Hi, I am stuck on something for a couple days, I am almost about to give up. This looks simple, but I can't figure out. I hope I can get some help here. I am trying to do some symbolic and numerical derivations. Let me explain the problem. Let's say, I have a matrix as follows: > load <- matrix(c(3,0,1,4,1,3),nrow=3,ncol=2,byrow=TRUE) > > load [,1] [,2] [1,] 3 0

I am having trouble displaying a dendrogram of evolutionary relationships (a phylogram imported from the ape package) as the vertical component of a heatmap, but keeping the hierarchical clustering of the horizontal component. The relationships of the vertical component in the generated heatmap are not that of the dendrogram, although the ordering is. In more detail, I am attempting to generate

I'm not entirely sure what caused this, but the following code, which used to behave as expected, is now broken: ---- lolwut.c ---------------------------- void lolwut(void) { __asm __volatile ( "ldr r1, =1f \n" ".ltorg \n" "1: \n\t" : : : "r0", "r1" ); } ------------------------------------------- ~/clang

1. (Mainly) Statistical issues are generally off topic on this list. You might want to try the r-sig-mixed-models list instead. 2. However, I think a better answer is to seek local statistical expertise in order to have an extended discussion about your research intent in order to avoid producing yet more irreproducible psychological research. Cheers, Bert Bert Gunter "The trouble with

I'm using specify.model for the sem package. I can't figure out how to represent the residual errors for the observed variables for a CFA model. (Once I get this working I need to add some further constraints.) Here is what I've tried: model.sa <- specify.model() F1 -> X1,l11, NA F1 -> X2,l21, NA F1 -> X3,l31, NA F1 -> X4,l41, NA F1 -> X5, NA, 0.20

I answer my own question: I had overlooked the fact that the normalization factor is also a function of the parameters I want to optimise, hence I should write dbeta2 <- function(x, shape){ res <- x^(shape-1)*(1-x)^(shape-1)/beta(shape, shape) return(res) } after which the results are consistent. ---------- Forwarded message ---------- From: Lorenzo Isella <lorenzo.isella

Dear All, I need to fit a custom probability density (based on the symmetric beta distribution B(shape, shape), where the two parameters shape1 and shape2 are identical) to my data. The trouble is that I experience some problems also when dealing with the plain vanilla symmetric beta distribution. Please consider the code at the end of the email. In the code, dbeta1 is the density of the beta

Hi all, I appreciate that this is not an RSpec question, but I wondered if anyone out there can offer some pointers. We''re using the latest versions of RSpec and RCov, and ruby --version says this (on the Ubuntu build server): ruby 1.8.6 (2008-07-17 patchlevel 279) [x86_64-linux] We''re getting intermittent (yes, intermittent!) segfaults from the build when running

Hello guys, I was looking forward to participate in GSoc14. I have a decent knowledge about c++ and parsers. I was looking at the idea pages where I found many interesting projects, in which "clustering of search results" interests me the most. I want someone to take me to the right track in understanding the project so that I can think about its implementation. According to me, in this

Hi, I´m trying to write some R classes but I din´t find documentation enought to develop them. I read there is 2 ways to write classes, using S3 ou S4 models. And it seems that S4 is the best model, so I thing I should use this one. I´m new user of R and I´m searched on the net some information about creating new classes. I found this document: