search for: relatedness

...bjects on the search path, which is not quite what I need: I want some way to list all non-local variables that increment() uses in its body. [The original variable names referred to genetic bandsharing data for possums, eg coates.female.pouchyoung.allbands.method5 and huapai.young.male.sibling.relatedness.method3 and huapai.old.female.nonsibling.relatedness.justdarkbands.method1 ad nauseum...hence the need for shorter example variable names!] ll1 <- 2 #sic increment <- function(x) { l11 <- 1 #sic return(x+ll1) #sic; deliberate bug here (sic) } -- Robin Han...

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 = m...

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 del...

...usly) 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 the genetic random effects between observations are given by the different degrees of relatedness between the individuals examined. (I find it difficult to explain, but Pettay et al. describe it nicely in their methods section...) Is there any straight-forward way to fit such a model with R? I first thought I could handle it somehow with nlme's correlation structures, but these within-grou...

...e! Robbert #data example inp3<-data.frame(group=rep(LETTERS[1:4],4), GF=as.vector(sapply(1:4,function(x)rep(x,4))), val=c(rep(c(2,3,7,8),2),rep(c(2,3,7,8),2)*1.1)) require(lattice) #this works fine, without second y-axis: xyplot(val~GF,groups=group, data=inp3,type="o", ylab="Relatedness", xlab="genotyped fraction", par.settings=simpleTheme(pch=c(1,2,3,4),lty=c(1,2),lwd=2,cex=1.5), auto.key=list(draw=TRUE,points=TRUE,lines=TRUE, text=LETTERS[1:4])) #to set a second y-axis with an other scale: # convert data to proper scale: inp3[which(inp3$group==&...

...ow being a dyad. The teaching types are not mutually exclusive. They can co-occur. This is why I am using a multi-response model but not a multi-nomial model. Focals as well as others can appear in more than one dyad, so I have included those as random effects. The fixed effects in the model are r (relatedness) and present (# observations together). I've specified my model as follows: m3.random.present.r <- MCMCglmm(cbind(Opp_teacher , Dir_teacher, Enh_teacher, SocTol_teacher, Eval_teacher) ~ +present + r + trait -1, random = ~ other + focal, prior = prior.m3,...

...lab= "Species", main = "heatmap of species present in environments") However, instead of a dendrogram that groups the rows (vertical axis) by the abundance pattern (as above), I would like to force it to order and display a dendrogram indicating their evolutionary relatedness. I am using the excellent ape package (http://cran.r-project.org/src/contrib/Descriptions/ape.html) to import the evolutionary dendrograms. I have already manipulated the dendrogram to be ultrameric, with branches all the same length, to prevent an error, although I would prefer not to have to do...

...art (one word > changed is a small distance; no words in common is a long way apart). > > Clustering is then splitting the documents into groups which are near > each other in that space. > So, here indirectly you are talking about is the vector space model where we will measure the relatedness between the sets on the basis of their Euclidean distances. Thus, using k-means algorithm ? > Set expansion would mean picking some seed documents to start the sets, > and then going through the remaining documents adding them to the > "nearest" set (by some measure). These se...

...> teaching types are not mutually exclusive. They can co-occur. This is why I > am using a multi-response model but not a multi-nomial model. Focals as > well as others can appear in more than one dyad, so I have included those > as random effects. The fixed effects in the model are r (relatedness) and > present (# observations together). > > I've specified my model as follows: > > m3.random.present.r <- MCMCglmm(cbind(Opp_teacher , Dir_teacher, > Enh_teacher, SocTol_teacher, Eval_teacher) ~ +present + r + trait -1, > random = ~ other + focal, >...

Some students of mine are trying to use gnls, the generalized non-linear least squares function within the nlme library, to study evolutionary questions where correlations between traits at the species level are non-independent because of the evolutionary relatedness of the species. Specifically, they're using a non-linear function (log(sexual dimorphism) ~ log(a + b*variation in mating opportunities), an exponential spatial correlation function that depends on the phylogenetic distance between species [I hacked the library a little bit to allow one to...

...imal 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 the genetic random effects between > observations are given by the different degrees of relatedness between > the individuals examined. (I find it difficult to explain, but Pettay > et al. describe it nicely in their methods section...) > > Is there any straight-forward way to fit such a model with R? I first > thought I could handle it somehow with nlme's correlation structure...

...because I would need some advice on the following question. I am working on paternity in a monogamous bird species and I am performing analyses to check whether the probability for a male to be cuckolded (binary variable) depends on his body size, the body size of his female, the degree of genetic relatedness to his female and nest density around his own nest (all continuous variables). Since I have data for two years (2002 and 2003), I think that the best solution is to conduct a logistic regression for repeated measures. However, I am a bit worried to use my entire data set. Indeed, a few individuals...

...ut I''ve now gotten that to be almost real-time (5 minutes max). Plus I can re-index the entire database of 1M+ items in about 8 hours. The index is backed up nightly in case of a memcached server failure (we''re using 3). In addition to search, the search web service is used for relatedness and for something like bookmarks. So, is there anything out there that can touch these results and provide for virtually unlimited scale (no central controller)? Thanks in advance, Marc PS: Because of leaks in rmagick and its inferior performance compared to the Python Image Library, I'...

...are not mutually exclusive. They can co-occur. This is > why I > > am using a multi-response model but not a multi-nomial model. Focals as > > well as others can appear in more than one dyad, so I have included those > > as random effects. The fixed effects in the model are r (relatedness) and > > present (# observations together). > > > > I've specified my model as follows: > > > > m3.random.present.r <- MCMCglmm(cbind(Opp_teacher , Dir_teacher, > > Enh_teacher, SocTol_teacher, Eval_teacher) ~ +present + r + trait -1, > >...

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

Hello All, I mentioned a problem with this once before, and was referred to other threads that also talked about this. But I believe a recent problem I was experiencing, may have been related to this: [: -le: argument expected. So I'd like to bring it up again, in hopes that someone might have a cure. Specifically, two printf()'s are sent to the same line, which results in a /very/ hard

Hello everyone, A long time ago, I posted the Stanford Best Practices and I''ve gone through and updated it today. I''d like to have people go through it and see if we can strip out some Stanford specific stuff and tag this as an official best practice. I think an official best practice will be important as more and more people consider making shareable modules, etc (mostly