Illustrates how network properties vary with the similarity threshold
Source:R/make-threshold-profile.R
make_threshold_profile.Rd
make_threshold_profile()
outputs properties of the agent or symbolic network
as a function of similarity threshold.
Arguments
- data
A data frame corresponding to the attitudes held by agents with respect to a number of items
- layer
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 indata
"symbolic"
produces the network corresponding to the symbols, or items, which we assume to be columns indata
Value
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 thresholdad
, the average degree resulting fromthreshold
, andlcc
, the size of the largest connected component resulting fromthreshold
Details
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.
Examples
S <- make_synthetic_data(20, 5)