generateNetwork(lambda_2 = 0.45, q = 10, min_phase_length = 1, k_bar = 5, l = 10, lambda_3 = 2, spacing = 1, gauss_weights = TRUE, same = FALSE, change_method = "sequential", fixed = FALSE, cps = NULL)
fixed=TRUE
, this is
equal to the number of changepoints.1
if segments are equally spaced, 0
if they are
spaced randomly (subject to the constraints of min_phase_length).1
if edge weights in the network are drawn from
N(0, 1), 0
if they are fixed to be 1.1
if all segments have the same network structure (no
changes), 0
otherwise.'sequential'
if the changes happen sequentially
(i.e. changes at segment i are applied to segment i-1),
'hierarchical'
if the changes happen with respect to a hypernetwork
(i.e. changes at segment i are applied to segment 0).T
if the changepoint locations are fixed, F
if
they should be sampled.simulateNetwork
# Generate random network with default parameters
network = generateNetwork()
# Simulate data using generated network
dataset = simulateNetwork(net=network)
# Generate random network with 4 changepoints and 15 nodes,
# with changepoints distributed over a timeseries of length 50
network = generateNetwork(l=50, q=15, fixed=TRUE, k_bar=4)
# Simulate data of length 50 using generated network
dataset = simulateNetwork(net=network)
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