plot.MNS: Plotting function for MNS objects

In MNS: Mixed Neighbourhood Selection

Description

Plotting function for MNS objects. This function implements plotting for either population networks, high variable networks or subject-specific networks.

Usage

  ## S3 method for class 'MNS'
plot(x, view="pop", subID=NULL, ...) 

Arguments

x	MNS object
view	Plotting view. This argument defines which networks are plotted. Three options are "pop": plot population network, "var": plot network of variable edges, "sub": plot subject-specific networks
subID	If view="sub", subID indicates which subjects networks should be plotted.
...	Additional arguments to pass to plot function

Details

Plotting function for MNS objects. Can be used to plot simulated networks or results obtained from running MNS algorithm. Note that if networks are simulated using the "Danaher" method then only subject-specific networks can be plotted (i.e., we require view="sub")

Author(s)

Ricardo Pio monti

References

Monti, R., Anagnostopolus, C., Montana, G. "Inferring brain connectivity networks from functional MRI data via mixed neighbourhood selection", arXiv, 2015

See Also

MNS, gen.Network

Examples

set.seed(1)
N=4
Net = gen.Network(method = "cohort", p = 10, 
                       Nsub = N, sparsity = .2, 
                       REsize = 20, REprob = .5,
                       REnoise = 1, Nobs = 10)
## Not run: 
# can plot simulated networks:
plot.MNS(Net, view="pop")

# can also plot results from MNS algorithm:
mns = MNS(dat = Net$Data, lambda_pop = .1, lambda_random = .1, parallel = TRUE)
plot.MNS(mns) # plot population network
plot.MNS(mns, view="var") # plot variance network
plot.MNS(mns, view="sub") # plot subject networks (note red edges here are variable edges!)

## End(Not run)

MNS documentation built on May 2, 2019, 9:33 a.m.