Displaying 8 results from an estimated 8 matches for "bonpow".
2009 Apr 06
2
Bonpower Crashes Trying Sparse Matrix (Igraph)
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/igr...
2009 Apr 20
1
Matrix package,solve() errors and crashes
...s.
When I use bonacich power it goes out of memory
Error in get.adjacency.dense(graph, type = type, attr = attr, names =
names, :
At vector.pmt:409 : cannot reserve space for vector, Out of memory
I got help from IGRAPH community to use sparse Matrix
http://igraph.wikidot.com/r-recipes#toc6
bonpow.sparse <- function(graph, nodes=V(graph), loops=FALSE,
exponent=1, rescale=FALSE, tol=1e-07) {
## remove loops if requested
if (!loops) {
graph <- simplify(graph, remove.multiple=FALSE, remove.loops=TRUE)
}
## sparse adjacency matrix
d <- get.adjac...
2009 Apr 17
0
Matrix package,solve() errors and crashes"
....
When I use bonacich power it goes out of memory
Error in get.adjacency.dense(graph, type = type, attr = attr, names =
names, :
At vector.pmt:409 : cannot reserve space for vector, Out of memory
I got help from IGRAPH community to use sparse Matrix
http://igraph.wikidot.com/r-recipes#toc6
bonpow.sparse <- function(graph, nodes=V(graph), loops=FALSE,
exponent=1, rescale=FALSE, tol=1e-07) {
## remove loops if requested
if (!loops) {
graph <- simplify(graph, remove.multiple=FALSE, remove.loops=TRUE)
}
## sparse adjacency matrix
d <- get.adjac...
2009 May 15
1
Matrix package,solve() errors and crashes Please help
.../Bonacich%20Power.RData
>
Graph size
*Vertices: 20924
Edges: 146938
Directed: FALSE
No graph attributes.
Vertex attributes: name.
No edge attributes.
*
computer Configuration
*WIndows XP service Pack 3 .0 GB RAM*
I am using SPARSE matrix to solve the problem
This is the code I use to obtain bonpower using Sparse Matrix &
alternatively the code is in the following website
http://igraph.wikidot.com/r-recipes#toc6
*bonpow.sparse <- function(graph, nodes=V(graph), loops=FALSE,
exponent=1, rescale=TRUE, tol=1e-07) {*
* ## remove loops if requested
*
* ## spa...
2009 Jul 14
1
Error installing package sna
...html latex example
bicomponent.dist text html latex example
blockmodel text html latex example
blockmodel.expand text html latex example
bn text html latex example
bonpow text html latex example
******* Syntax error: \item in
/-----
Gould and Fernandez (following Marsden and others) describe
<EM>brokerage</EM> as the role played by a social actor who mediates contact
between two alters. More formally, vertex v is a b...
2012 Jun 18
0
igraph 0.6 released
...ector centrality. See centralization.scores().
- Personalized Page-Rank scores, see page.rank().
- Subgraph centrality, subgraph.centrality().
- Authority (authority.score()) and hub (hub.score()) scores support
edge weights now.
- Support edge weights in betweenness and closeness calculations.
- bonpow(), Bonacich's power centrality and alpha.centrality(),
Alpha centrality calculations now use sparse matrices by default.
- Eigenvector centrality calculation, evcent() now works for
directed graphs.
- Betweenness calculation can now use arbitrarily large integers,
this is required for som...
2012 Jun 18
0
igraph 0.6 released
...ector centrality. See centralization.scores().
- Personalized Page-Rank scores, see page.rank().
- Subgraph centrality, subgraph.centrality().
- Authority (authority.score()) and hub (hub.score()) scores support
edge weights now.
- Support edge weights in betweenness and closeness calculations.
- bonpow(), Bonacich's power centrality and alpha.centrality(),
Alpha centrality calculations now use sparse matrices by default.
- Eigenvector centrality calculation, evcent() now works for
directed graphs.
- Betweenness calculation can now use arbitrarily large integers,
this is required for som...
2009 Jun 29
5
Help
HiĀ group,
I found a module for adaptive kernel density estimation for Stata users, but unfortunetly I don't have access to Stata, can I find a similar approach using R?
Thank u so much 4 ur time.
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