Compute the robustness of an ecological network by averaging over a great number of randomly generated primary extinctions sequences
robustness_emp(
A,
ext_seq = "uniform",
nb_iter = 300,
net_type = "bipartite",
method = "ordered",
power = 1,
block = NULL
)
A binary incident matrix
A string, the rule for the primary extinctions sequences,
one of "uniform"
, the default for uniform extinctions sequences,
"decreasing"
and "increasing"
for primary extinctions sequences
by increasing and decreasing degree order sequence on the row species
An integer, the number of generated sequences. Default to
300
.
A string, the type of network. For now, only "bipartite" is available.
A string used when ext_seq = "decreasing"
or
ext_seq = "increasing"
:
"linear"
(default) set an extinction
probability for each row species that is linear in its degree. It is a
shortcut for method = "power"
and power = 1
.
"ordered"
strictly follow the degree order, i.e. the most
connected species will always goes last for ext_seq = "increasing"
or first for ext_seq = "decreasing"
.
An integer (default to 1). Only used when
method = "power"
,
the power to which the degree are elevated to compute the primary extinctions
sequences for "increasing"
and "decreasing"
ext_seq. For 1, it
is equivalent to method = "linear"
, for 0, it is the same as
ext_seq = "uniform"
. The largest the number the closest it will be to
method = "ordered"
.
A vector of row species memberships for method = "block"
A list (robber object) with the following fields:
$model
, $ext_seq
, $method
, power
$fun
is the robustness function, a vector of size (nrow(A) +1)
$sd
Standard deviation of the secondary extinctions
$auc
the area under the curve of the robustness function