make_threshold_profile() outputs properties of the agent or symbolic network
as a function of similarity threshold.
make_threshold_profile(
data,
layer = NULL,
comparisons = NULL,
metric = NULL,
count = NULL,
limits = NULL,
dummycode = NULL,
...
)A data frame containing properties of the agent or symbolic network as a
function of the similarity threshold. In particular, it contains three columns
named
threshold, the value of the similarity threshold
ad, the average degree resulting from threshold, and
lcc, the size of the largest connected component resulting from
threshold
A data frame corresponding to the attitudes held by agents with respect to a number of items
A string flag specifying the type of network to be extracted,
"agent" produces the network corresponding to the agents, which we assume
to be rows in data
"symbolic" produces the network corresponding to the symbols, or items,
which we assume to be columns in data
An integer, minimum number of comparisons for valid distance.
A string option describing the similarity metric to be used.
The number of threshold values to include in the description.
Specify the limits of the Likert range in during a data preprocessing step.
Specify whether to apply dummycoding during a data preprocessing step.
Used to handle alternative argument spellings.
Note that this routine is expensive on large graphs. We study networks over the
full range of similarity thresholds [-1, 1], and as a result, produce
networks that are complete at the lower limit of that range. Note that by default we
will subsample the provided survey with the C++ implementation in order to
avoid memory issues. We could then allow a flag that turns off the subsampling
step, at the user's peril.
S <- make_synthetic_data(20, 5)
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