Description Usage Arguments Examples
Generates list of degree sequences and summary statistics for a mechanistic model
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | net_ss(
theta_m,
replicates = 1000,
sorted = TRUE,
mech_net,
lstat,
lapply_opt = TRUE,
ergm = FALSE
)
process_ss(
g,
theta_s,
mirror,
type = "Bianconi",
entropy_ss = FALSE,
degree_triangle = FALSE
)
KL_ss(
theta_m,
theta_s,
mirror = TRUE,
type = "Bianconi",
entropy_ss = FALSE,
degree_triangle = FALSE,
...
)
KL_net(theta_m, ...)
|
theta_m |
numeric mechanistic model parameters |
replicates |
numeric number of replicates |
sorted |
logical whether to consider the sorted or unsorted degree sequence as the integral statistic |
mech_net |
function the mechanistic network simulator |
lstat |
function computes the likelihood statistic |
lapply_opt |
boolean internal |
g |
output of 'net_ss' |
theta_s |
statistical parameter |
mirror |
Boolean. whether base measure should be mirrored |
type |
String: either "Liebenau" or "Bianconi" |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | library(StartNetwork)
n = 15
replicates = 400
mech_net_triangles <- purrr::partial(mech_net_triangles_n, n = !!n)
lstat = function(x){length(igraph::triangles(x))/3}
x = net_ss(
theta_m = 0.3,
replicates = 50,
mech_net = mech_net_triangles,
lstat = lstat
)
y = process_ss(x, 0.5, mirror = TRUE)
reprocess_ss(y, 0.6)
|
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