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how to add an edgecov() ergmm model term in latentnet package in R

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0

I have a temporal bipartite network of authors and topics, I am making a ML model which includes a term which must represent the edge persistence feature.
I am using latentnet package in R.

So, i have added a network attribute named "edge_persistence" and am trying to add a edgecov() term. I am getting this error when i include this edgecov() term.

Error in xa[cbind(pl$xmat[, 1:2, drop = FALSE], k)] <- pl$xmat[, k +
2] : subscript out of bounds

Here is the partial source code:

#creating the network
net <- network(year_matrix, vertex.attr = NULL, vertex.attrnames = NULL, directed = FALSE, hyper = FALSE, loops = FALSE, multiple = FALSE, bipartite = 2)

#calculating the number of edges
no_of_edges = 0
for(i in c(1:length(author_nodes)))

 for(j in c(1:length(topic_nodes)))
 
 no_of_edges = no_of_edges+1
 


#forming the edge_persistance_vector
edge_persistance_vector <- vector("numeric", no_of_edges)
temp_itr=1
for(i in c(1:length(author_nodes)))

 for(j in c(1:length(topic_nodes)))
 
 if(year_matrix[i, j]==1)
 
 if(prev_year_matrix[i, j]==1)
 
 edge_persistance_vector[temp_itr] = 1
 
 else
 
 edge_persistance_vector[temp_itr] = 0
 
 
 else
 
 edge_persistance_vector[temp_itr] = 0
 
 temp_itr = temp_itr+1
 


#adding the network attribute
set.network.attribute(net, attrname = "edge_persistance", value = edge_persistance_vector)

#making the model
ergmm_result <- ergmm(formula = net ~ euclidean(d=2, G=3) + rsociality(var=1, var.df=3) + edgecov("edge_persistance"), verbose = TRUE) 

And here is the error which I am getting if I include the edgecov("edge_persistance") term

Error in xa[cbind(pl$xmat[, 1:2, drop = FALSE], k)] <- pl$xmat[, k +
2] : subscript out of bounds

Can someone please suggest how I can resolve this "subscript out of bounds" error?
Thanks in advance!!

r social-networking statnet

share|improve this question

edited Mar 25 at 12:37

jacky_learns_to_code

49722 gold badges77 silver badges2121 bronze badges

asked Mar 25 at 12:21

Bhanu vikas YagantiBhanu vikas Yaganti

444 bronze badges

add a comment | 

0

I have a temporal bipartite network of authors and topics, I am making a ML model which includes a term which must represent the edge persistence feature.
I am using latentnet package in R.

So, i have added a network attribute named "edge_persistence" and am trying to add a edgecov() term. I am getting this error when i include this edgecov() term.

Error in xa[cbind(pl$xmat[, 1:2, drop = FALSE], k)] <- pl$xmat[, k +
2] : subscript out of bounds

Here is the partial source code:

#creating the network
net <- network(year_matrix, vertex.attr = NULL, vertex.attrnames = NULL, directed = FALSE, hyper = FALSE, loops = FALSE, multiple = FALSE, bipartite = 2)

#calculating the number of edges
no_of_edges = 0
for(i in c(1:length(author_nodes)))

 for(j in c(1:length(topic_nodes)))
 
 no_of_edges = no_of_edges+1
 


#forming the edge_persistance_vector
edge_persistance_vector <- vector("numeric", no_of_edges)
temp_itr=1
for(i in c(1:length(author_nodes)))

 for(j in c(1:length(topic_nodes)))
 
 if(year_matrix[i, j]==1)
 
 if(prev_year_matrix[i, j]==1)
 
 edge_persistance_vector[temp_itr] = 1
 
 else
 
 edge_persistance_vector[temp_itr] = 0
 
 
 else
 
 edge_persistance_vector[temp_itr] = 0
 
 temp_itr = temp_itr+1
 


#adding the network attribute
set.network.attribute(net, attrname = "edge_persistance", value = edge_persistance_vector)

#making the model
ergmm_result <- ergmm(formula = net ~ euclidean(d=2, G=3) + rsociality(var=1, var.df=3) + edgecov("edge_persistance"), verbose = TRUE) 

And here is the error which I am getting if I include the edgecov("edge_persistance") term

Error in xa[cbind(pl$xmat[, 1:2, drop = FALSE], k)] <- pl$xmat[, k +
2] : subscript out of bounds

Can someone please suggest how I can resolve this "subscript out of bounds" error?
Thanks in advance!!

r social-networking statnet

share|improve this question

edited Mar 25 at 12:37

jacky_learns_to_code

49722 gold badges77 silver badges2121 bronze badges

asked Mar 25 at 12:21

Bhanu vikas YagantiBhanu vikas Yaganti

444 bronze badges

add a comment | 

I have a temporal bipartite network of authors and topics, I am making a ML model which includes a term which must represent the edge persistence feature.
I am using latentnet package in R.

So, i have added a network attribute named "edge_persistence" and am trying to add a edgecov() term. I am getting this error when i include this edgecov() term.

Error in xa[cbind(pl$xmat[, 1:2, drop = FALSE], k)] <- pl$xmat[, k +
2] : subscript out of bounds

Here is the partial source code:

#creating the network
net <- network(year_matrix, vertex.attr = NULL, vertex.attrnames = NULL, directed = FALSE, hyper = FALSE, loops = FALSE, multiple = FALSE, bipartite = 2)

#calculating the number of edges
no_of_edges = 0
for(i in c(1:length(author_nodes)))

 for(j in c(1:length(topic_nodes)))
 
 no_of_edges = no_of_edges+1
 


#forming the edge_persistance_vector
edge_persistance_vector <- vector("numeric", no_of_edges)
temp_itr=1
for(i in c(1:length(author_nodes)))

 for(j in c(1:length(topic_nodes)))
 
 if(year_matrix[i, j]==1)
 
 if(prev_year_matrix[i, j]==1)
 
 edge_persistance_vector[temp_itr] = 1
 
 else
 
 edge_persistance_vector[temp_itr] = 0
 
 
 else
 
 edge_persistance_vector[temp_itr] = 0
 
 temp_itr = temp_itr+1
 


#adding the network attribute
set.network.attribute(net, attrname = "edge_persistance", value = edge_persistance_vector)

#making the model
ergmm_result <- ergmm(formula = net ~ euclidean(d=2, G=3) + rsociality(var=1, var.df=3) + edgecov("edge_persistance"), verbose = TRUE) 

And here is the error which I am getting if I include the edgecov("edge_persistance") term

Error in xa[cbind(pl$xmat[, 1:2, drop = FALSE], k)] <- pl$xmat[, k +
2] : subscript out of bounds

Can someone please suggest how I can resolve this "subscript out of bounds" error?
Thanks in advance!!

r social-networking statnet

share|improve this question

edited Mar 25 at 12:37

jacky_learns_to_code

49722 gold badges77 silver badges2121 bronze badges

asked Mar 25 at 12:21

Bhanu vikas YagantiBhanu vikas Yaganti

444 bronze badges

#creating the network
net <- network(year_matrix, vertex.attr = NULL, vertex.attrnames = NULL, directed = FALSE, hyper = FALSE, loops = FALSE, multiple = FALSE, bipartite = 2)

#calculating the number of edges
no_of_edges = 0
for(i in c(1:length(author_nodes)))

 for(j in c(1:length(topic_nodes)))
 
 no_of_edges = no_of_edges+1
 


#forming the edge_persistance_vector
edge_persistance_vector <- vector("numeric", no_of_edges)
temp_itr=1
for(i in c(1:length(author_nodes)))

 for(j in c(1:length(topic_nodes)))
 
 if(year_matrix[i, j]==1)
 
 if(prev_year_matrix[i, j]==1)
 
 edge_persistance_vector[temp_itr] = 1
 
 else
 
 edge_persistance_vector[temp_itr] = 0
 
 
 else
 
 edge_persistance_vector[temp_itr] = 0
 
 temp_itr = temp_itr+1
 


#adding the network attribute
set.network.attribute(net, attrname = "edge_persistance", value = edge_persistance_vector)

#making the model
ergmm_result <- ergmm(formula = net ~ euclidean(d=2, G=3) + rsociality(var=1, var.df=3) + edgecov("edge_persistance"), verbose = TRUE) 

share|improve this question

edited Mar 25 at 12:37

jacky_learns_to_code

49722 gold badges77 silver badges2121 bronze badges

asked Mar 25 at 12:21

Bhanu vikas YagantiBhanu vikas Yaganti

444 bronze badges

share|improve this question

edited Mar 25 at 12:37

jacky_learns_to_code

49722 gold badges77 silver badges2121 bronze badges

asked Mar 25 at 12:21

Bhanu vikas YagantiBhanu vikas Yaganti

444 bronze badges

edited Mar 25 at 12:37

jacky_learns_to_code

49722 gold badges77 silver badges2121 bronze badges

edited Mar 25 at 12:37

jacky_learns_to_code

49722 gold badges77 silver badges2121 bronze badges

asked Mar 25 at 12:21

Bhanu vikas YagantiBhanu vikas Yaganti

444 bronze badges

asked Mar 25 at 12:21

Bhanu vikas YagantiBhanu vikas Yaganti

444 bronze badges