search for: hierarchal

I've been using sna to work with some networks, and am trying to visualize them easily. My networks are hierarchical (food webs). All of the layout engines I've tried with gplot don't seem to plot hierarchical networks, as one would using dot from graphviz. While I could do all of this by outputting to dotfiles and running it through graphviz, the graphics I get from R are much

Is there a way to do hierarchical (bayesian) logistic regression in R, the way we do it in BUGS? For example in BUGS we can have this model: model {for(i in 1:N) { y[i] ~ dbin(p[i],n[i]) logit(p[i]) <- beta0+beta1*x1[i]+beta2*x2[i]+beta3*x3[i] } sd ~ dunif(0,10) tau <- pow(sd, -2) beta0 ~ dnorm(0,0.1) beta1 ~ dnorm(0,tau) beta2 ~ dnorm(0,tau) beta3 ~

Hi Friends, I'm trying to model the consumer decisions (Click-Through Rate and Conversion) in Search Engine Advertising using a hierarchical Bayesian binary logit. The input data is the weekly CTRs and Avg. Position for each search keyword. CTR is modeled as (for each keyword i and week j): Pij = exp(C + Bi x Positionij + A1 x Lengthi + A2 x Brandi + A3 x ProductSpecifici) / [1 + exp(C +

Hello, I am in the process of trying to date hierarchical data in a MySQL database and convert it into a treeview view JS scripting. As a beginner to ROR there are still many unknown things to me, and handling this sort of data is one of them. My question is this: Is there any built in functionality for handling hierarchical data (via a MySQL DB) in Rails/Ruby? If there is can someone please

I would appreciate any information about how to carry out a hierarchical cluster analysis with cluster of subjects. I need to find cluster of subjects that share many variables. I know that fcp package have a lot of options to carry out the regular hierarchical cluster analysis (cluster of variables). Thank´s in advance Juan Hernández Facultad de Psicología La Laguna University Canary Islands

Hi, I am facing a hierarchically structured dataset, and I am not sure of the right way to analyses it with cforest, if their is one. - - BACKGROUND & PROBLEM We are analyzing the behavior of some social birds facing different temperature conditions. The behaviors of the birds were recorder during many sessions of 2 hours. Conditional RF (cforest) are quite useful for this analysis

hi, I want to do hierarchical clustering with Jaccord index. I tried to do with vegan package for finding index and hierarchical clustering with hclust function. While doing clustering it is showing an error message as "invalid distance method". I would be grateful if anyone tells how to rectify the error. Thanks in advance,   kind regards, Ms.Karunambigai M PhD Scholar Dept. of

Dear R users, I would like to fit cross classified or multiple membership logistic models or a 3 level hierarchical logistic model using the Umacs package. Can anyone advise me on how to proceed or better point me to examples of how its done. Regards, -- Luwis Diya, Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat), Kapucijnenvoer 35 blok d - bus 7001, 3000 Leuven,

dear colleagues, I want to use hierarchical partitioning methods to evaluate variance contributions of differente predictors within a generalized linear mixed model framework. I don't know if this is possible, because I can not found anything about this issue. My error is poisson and I, at least, a random factor in the designed analysis. I acknowledge any idea about how deal with

Hi there, is there any R-function for k-nearest neighbour agglomerative hierarchical clustering? By this I mean standard agglomerative hierarchical clustering as in hclust or agnes, but with the k-nearest neighbour distance between clusters used on the higher levels where there are at least k>1 distances between two clusters (single linkage is 1-nearest neighbour clustering)? Best regards,

Dear R users, Is there a way to apply a “stopping rule” in hierarchical Clustering? I have a data and I want to find the optimal number of clusters while doing hierarchical clustering. I would be deeply obliged if someone, whoever applied stopping rule, could send me the scripts. thanks in advance Regards Eliza botto [[alternative HTML version deleted]]

This is a question about how to calculate similarities/distances among items that are classified by hierarchical attributes for the purpose of visualizing the relations among items by means of clustering, MDS, self-organizing maps, and so forth. I have a set of ~260 items that have been classified using two sets of hierarchically-organized codes on the basis of form and content. The data looks

Hi all I have a hopefully not too stupid question about multi-level / mixed-effects modeling. I was trying to test a strategy from Crawley's 2013 R Book on a data set with the following structure: - dependent variable: CONSTRUCTION (a factor with 2 levels) - independent fixed effect: LENGTH (an integer in the interval [1, 61]) - random effects with the following hierarchical structure: MODE

Hey Everyone! I wanted to carry out Hierarchical clustering using distance matrices i have calculated ( instead of euclidean distance etc.) I understand as.dist is the function for this, but the distances in the dendrogram i got by using the following script(1) were not the distances defined in my distance matrices. script: var<-read.table("the distance matrix i calculated",

Dear Dr. Liaw Andy: I have a few more questions about your heatmap function. actually heatmap is what I am looking for. heatmap(x, Rowv, Colv, distfun = dist, hclustfun = hclust, add.expr, scale=c("row", "column", "none"), na.rm = TRUE, ...) my data is a XNEW, > dim(XNEW) [1] 554 335 554 genes, 335 samples. now I want to use 1-CORR as a distance

I would like to fit a 2-level mixed model: yit=a+a[i]+a[it] +(b+b[i]+b[it])*xit+eps[it] However, the variance of the second level components should depend on the group, i.e. sigma for a[it] and b[it] should be [i] specific. I do not know whether this is conceptually right in the mixed model context... In case it stands, how should the formula look like? Also, the data are unbalanced with

Hi I would like to run a multi-level hierarchical logistic regression model with sampling weight? Is this possible with R? Thanks a lot, Qian Guo --------------------------------- [[alternative HTML version deleted]]

Hi R users! I have a bit of a problem with using an hierarchical clustering algorithm: a<-c(1:15) b<-rep(seq(1:3), 5) c<-rnorm(15, 0,1) d<-c(sample(1:100, 15, replace=T)) e<-c(sample(1:100, 15, replace=T)) f<-c(sample(1:100, 15, replace=T)) data<-data.frame(a,b,c,d,e,f) q<-data.frame(data$d, data$e, data$f) q<-scale(q) What i want to do is to use an

Hello List, I am trying to implement a hierarchical cluster using the hclust method agglomerative single linkage method with a small wrinkle. I would like to cluster a set of numbers on a number line only if they are within a distance of 500. I would then like to print out the members of this list. So far I can put a vector: > x<-c(2,10,200,300,600,700) into a distance matrix: >

Hello All, I need to calculate cumulative lengths along a hierarchical network topology (it's a representation of a tree). I can roll my own, but thought that there might be a package out there that would handle hierarchical network topology functions such as this nicely (and that might bring along other useful functions as well). However, I haven't found one after searching. I