Description Usage Arguments Value Examples
simulate multiple sparse graphs and generate samples
1 | simulation(p = 20, n, seedNum = 37, s = 0.1, ss = 0.1)
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p |
number of features (number of nodes) |
n |
a vector indicating number of samples and tasks, for example c(100,200,300) for 3 tasks and 100,200 and 300 samples for task 1, 2 and 3 |
seedNum |
seed number for random simulation |
s |
positive number that controls sparsity of the generated graphs |
ss |
positive number that controls sparsity of the shared part of generated graphs |
a list comprising $simulatedgraphs (multiple related simulated graphs) and $simulatedsamples (samples generated from multiple related graphs)
1 2 3 | library(JointNets)
simulateresult = simulation(p = 20, n = c(100,100))
plot(simulateresult$simulatedgraphs)
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