Dear all,
I am new to network analysis, but since I have good data I started to read
about it and learned how to use the ergm and related packages. I generally
get interesting results, but when I run a model including sociality and
selective mixing effects for different groups, the model runs (and
converges) but I get a warning as follows:
mod <- ergm(network ~ edges + gwesp(0, fixed=T) + nodefactor("code") +
nodematch("code", diff=T)+ nodecov("vulnEVI") + absdiff("vulnEVI"))
Observed statistic(s) nodematch.code.5, nodematch.code.6, and
nodematch.code.8 are at their smallest attainable values. Their coefficients
will be fixed at -Inf.
The model nevertheless runs and converges and produces the following output:
==========================
Summary of model fit
==========================
Formula: network ~ edges + gwesp(0, fixed = T) + nodefactor("code") +
nodematch("code", diff = T) + nodecov("vulnEVI") + absdiff("vulnEVI")
Iterations: 20
Monte Carlo MLE Results:
Estimate Std. Error MCMC % p-value
edges -5.34531 0.66468 NA < 1e-04 ***
gwesp.fixed.0 2.17907 0.27527 NA < 1e-04 ***
nodefactor.code.3 -0.19424 0.20055 NA 0.33283
nodefactor.code.4 -0.45733 0.21730 NA 0.03538 *
nodefactor.code.5 -0.49081 0.22815 NA 0.03151 *
nodefactor.code.6 -1.19468 0.25695 NA < 1e-04 ***
nodefactor.code.7 -1.26290 0.24369 NA < 1e-04 ***
nodefactor.code.8 -1.26365 0.38244 NA 0.00096 ***
nodematch.code.2 0.10071 1.31137 NA 0.93879
nodematch.code.3 2.70398 0.53684 NA < 1e-04 ***
nodematch.code.4 0.67157 0.26456 NA 0.01117 *
nodematch.code.5 -Inf NA NA NA
nodematch.code.6 -Inf NA NA NA
nodematch.code.7 0.58640 0.81906 NA 0.47407
nodematch.code.8 -Inf NA NA NA
nodecov.vulnEVI 0.22562 0.07024 NA 0.00133 **
absdiff.vulnEVI -0.01086 0.11925 NA 0.92742
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
Hence the model is unable to obtain estimates for three of the groups and I
don't understand why. When I include the nodematch with diff=F there is no
problem (although of course I only get one coefficient). Does anyone know
what the problem might be? At first I though there might not be any edges
connecting members of groups 5, 6, and 8, but I checked this and they
certainly do cooperate among them. Any help would be greatly appreciated.
Thank you!
Best,
Florian
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ergm model, nodematch with diff=T
3 messages · Florian Weiler, ya
Hi all,
I have a question about using bigmemory package.
Here is my code:
>
x=read.big.matrix("acc3.dat",backingfile="acc3.bin",descriptorfile="acc3.desc",type="double")
Error in filebacked.big.matrix(nrow = nrow, ncol = ncol, type = type, :
A big.matrix must have at least one row and one column
And here is the example code:
> x <- read.big.matrix("airline.csv", header=TRUE,
+ backingfile="airline.bin",
+ descriptorfile="airline.desc",
+ type="integer")
So, what was wrong? Any suggestions please?
Thank you very much.
ya
Hi all, In addition, I am planning to do a multiple imputation with MICE package using the data read by bigmemory package. So usually, the multiple imputation code is like this: > imp=mice(data.frame,m=50,seed=1234,print=F) the data.frame is required. How can I change the big.matrix class generated by bigmemory package to a data.frame? Thank you very much. ya