similar to: Welcome to the "R-help" mailing list (Digest mode)

Dear colleagues, I'm trying to have a look at the Assortative and Disassortative ( http://en.wikipedia.org/wiki/Assortative_mixing) of the network I have. But it seems that the igraph hasn't mentioned that yet. I have to get the in/out degree of the vertices of each edge and calculate the Pearson's Correlation coefficient which seems to be quite a huge task for me. :( So I wonder if

Hi all, I have two networks for the same group of the users. I want to compare individual's degree in different networks. But how could I get the degrere of the nodes according to its name? When I use degree(g1), I could only get a vector of the degree of each node. But when I turn to g2, I don't know whose degree it is so I can't match it with the degree(g2). Now I'm trying to

Hi all, Is there anyone who ever used igraph to calculate the index of "centralization" ? I tried my best but can't find it in igraph. The brief introduction to "centralization" can be found here , and I think it's an important index for measuring the centrality on the aggregated level.(http://faculty.ucr.edu/~hanneman/nettext/C10_Centrality.html) Thank you for any

Dear all, I'm using igraph for some analysis about the network I have. I have a question about the function "power.law.fit". I wonder if there is any test for checking whether the "power.law.fit" is good for the input, i.e., under which situation, could we use this function to get a reliable result. I'm afraid even I input a random graph without any property of

Hi R-users, I'm using igraph for an undirected graph. i used clusters() igraph function to know the component size(subgraphs) as shown bellow: c <-clusters(g)    # component sizes size <- sort(c$csize, decreasing=TRUE) cat("Top 20 cluster of the graph","\n") for (i in 1:20) {   cat(i,"  size:",size[i] ,"\n") } Can anyone help how to extract the

Dear all, I have a undirected network (g), representing all the sexual relationships that ever existed in a model community. I also have a directed edgelist (e) which is a subset of the edgelist of g. e represents the transmission pathway of HIV. Now I would like to superimpose the picture of the sexual relationships with arrows in a different colour, to indicate where in the network HIV was

Hey all, I'm looking for a plotting method for two-mode networks. Having a n x m matrix where n is the first set of entities/ actors and m representing the second set, I want to colour both sets of actors differently. I tried "plot.network" from the network-package, but I did not succeed. Even the proposed solution from Gabor Grothendiek

On Thu, Jan 31, 2013 at 10:29 AM, Weijia Wang <wwang.nyu@gmail.com> wrote: > Hi, > > > > I have a new question about subsetting in R. > > > > Say we have this data frame: > > > > PT_ID Blood_Pressure OBS_TYPE > > 92 1900 90.0 DBP > > 94 1900 90.0 DBP > > 174 2900 140.0 SBP > > 176 2900

Hi, So I've been figuring out how to use igraph in R and like it for it's speed and simplicity. Now I have a graph built from an edgelist where vectors have a $name attribute. I have another dataframe with attributes tied to a vector ID, which is the same as the $name attribute of vectors represented in the graph. How can I iterate over the graph by V(g)$name and do

Hi I am using R with igraph to analyze an edgelist that is greater than the said amount. Does anyone know a way around this? Thanks Inder

Hi everyone, I have a dataset of friendship with this format: ego alter 4746 1 2 9742 1 3 14738 1 NA 4747 2 NA 9743 2 3 14739 2 1 4748 3 13 9744 3 5 14740 3 14 4749 4 NA 9745 4 NA 14741 4 NA 4750 5 NA 9746 5 13 14742 5 10 4751 6 12 9747 6 7 ... NA means that individuals don't select any

Hi, I have network data in the form of a couple of edgelists containing weights in the format "x,y,weight" whereby x represents row header and y represents column header. All edgelists are based on links among 634 nodes and I need to convert them into a 634*634 weighted matrix. I searched for online help using possible keywords I know, but I could not find a clue how to do this in

I'm interested in computing densities of a number of small ego-centred or local networks. I've installed both the R program and the sna package. My next task is importing the data into R. Our data was entered into Spss in an edgelist format in which each case specifies the link between an alter and an ego. For example: 10101 10102 1 10101 10103 3 10102 10104 2 10201 10203

Hello All, I have been trying to do bonpow for a while now.Bonpow works for few graphs and for few others it goes out of memory. I did see reply to one of the posting Alph Centrality Crashed in Igraph memory error. The solution in the posting was to use sparse matrix. This is the link of the message. http://lists.gnu.org/archive/html/igraph-help/2008-04/msg00071.html I was able to obtain

Hello All, I have had considerable bad luck with attempting the following with for loops. Here is the problem: # Suppose we have a data.frame with the following data, which can be considered a type of edgelist (for those with networks backgrounds): # # V1 V2 # 1 A # 1 A # 1 B # 2 A # 3 C # 3 A # 3 C # 3 B # # I want the output of the function to produce a matrix, such that #each factor of

Dear All, Some of the functions in Linkcomm return an error: unused argument(s) (v = V(x$igraph)) Although I follow the guidance in the manual a number of the functions return this error. The igraph vector is an edgelist. Many thanks for any guidance. Best, Nick

Hello everone, I am a computer science researcher in the UK - and have a quick question regarding importing data into R and more specifically latentnet. I am trying to import data such as a text file containing: (This is based on the Sampson data set) ----------- Network attributes: vertices = 3 directed = TRUE hyper = FALSE loops = FALSE multiple = FALSE total edges=

Dear R users I'm a novice user of R and have absolutely no prior knowledge of social network analysis, so apologies if my question is trivial. I've spent alot of time trying to solve this on my own but I really can't so hope someone here can help me out. Cheers! The dataset: I'm trying to predict the existance of links (True or False) in a test set using a training set. Both

**Hi, I wanted to create a network of drugs that are being studied together. So, I created a file as a graph. But plot of my network is not corect! It looks like to me that something else is lying behind this network links created. Could someone help me with this? Thanx! a<-read.graph(file=file.choose(), format="edgelist") plot.igraph(a) File (number present ID of drug): 15 2 10

I have a text file full of numbers (it's a edgelist for a graph) and I would like to recode the numbers as they are way too big to work with. So for instance the following: 676529098667 1000198767829 676529098667 100867672856227 676529098667 91098726278 676529098667 98928373 1092837363526 716172829 would become: 0 1 0 2 0 3 0 4 5 6 i.e. all 676529098667 would become