NAMESPACE does not include export("attribsim") - so the function cannot be used.

I have data that essentially looks like this:
Network, Seed size, Diffusion
i.e. a set of different networks and some data that goes along with each.

I'd like to run a regression, something like this:
Diffusion ~ Seed size + Clustering + Average path length + Number of components...

But instead can I use tnam to run a regression using the weighted network structure itself as an independent variable rather than extracting summary variables from the network data? Like this:
Diffusion ~ Seed size + Network

Hello, I intend to apply the tnam package in an academic research. More precisely, in a study on international trade networks (comtrade data). Would you like to know how the database should be built? For example data.frame or list? Do you have any models? Thanks.

Why is there no pathdist parameter on the weightlag term?

What might cause outdegree to always produce NA in the model summary in the analysis of a weighted network? At the same time, outdegree.degree0 produces results.

Dear all, I am new to tnam and looking for help.
I have a directed network with 91 actors (only one time point) and a number of actor's attributes. My data are rather sensitive, but I try to provide a minimal example here. The dependent variable here is named hetero.
This is the code
`library(statnet)
library(tnam)
library(texreg)

#read in network data#
tgnet <- read.csv("C:/Users/Anja Osei/Desktop/Togo data original/tgnet.csv", row.names=1, sep=";", stringsAsFactors=FALSE)
View(tgnet)
tgnet<-as.matrix(tgnet)
tgnet<-as.network(tgnet)
plot(togonet)

#read in attribute data#
tgexample <- read.csv("C:/Users/Anja Osei/Desktop/Togo data original/tgexample.csv", row.names=1, sep=";", stringsAsFactors=FALSE)

#set network attributes#
set.vertex.attribute(tgnet, "year", tgexample$year)

#minimal example using clustering and year#
model1<-tnam(tgexample$hetero~clustering(tgnet)+covariate(tgexample$year, coefname="year"))
summary(model1)

#using tnamdata, clustering produces NAs#
tnamdata(tgexample$hetero~clustering(tgnet)+covariate(tgexample$year, coefname="year"))

#if I add clustering as a covariate, it runs. I have exactly this problem with whatever I try, centrality, netlag... everything#
test<-clustering(tgnet)

model2<-tnam(tgexample$hetero~covariate(test$clustering, coefname="clustering")+covariate(tgexample$year, coefname="year"))
summary(model2)`

Files.zip

Thanks in advance for any suggestions.