Comments (3)
The problem is that netSimulator does not know what model to use in data generation (if you use default = "EBICglasso" it knows to generate a GGM). It should work with adding the argument dataGenerator = ggmGenerator()
. Note though that correlation networks do not aim to estimate a GGM and will likely show poor performance.
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Thank you for your reply.
Running this still yields an error message and a lot of warnings:
netSimulator(
input = genGGM(Nvar = 40),
nCases = c(50, 100, 250, 500, 1000, 2500),
nReps = 10,
default = c("cor", "TMFG"),
dataGenerator = ggmGenerator)
Error in match.arg(default) :
'arg' should be one of “none”, “EBICglasso”, “pcor”, “IsingFit”, “IsingSampler”, “huge”, “adalasso”, “mgm”, “relimp”
Any suggestions?
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ggmGenerator is a function. If you add () after it, it will use the default settings for the function, ie. (ordinal = FALSE, nLevels = 4). You can also adjust those values so that it better approximates the data you are interested in.
E.g., this will work
netSimulator(
input = genGGM(Nvar = 40),
nCases = c(50, 100, 250, 500, 1000, 2500),
nReps = 10,
default = c("cor", "TMFG"),
dataGenerator = ggmGenerator())
And this will make the data ordinal
netSimulator(
input = genGGM(Nvar = 40),
nCases = c(50, 100, 250, 500, 1000, 2500),
nReps = 10,
default = c("cor", "TMFG"),
dataGenerator = ggmGenerator(ordinal = T))
from bootnet.
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