ffluency: Fast verbal fluency generator
In memnet: Network Tools for Memory Research

Description Usage Arguments Details Value References Examples

Generates multiple verbal fluency sequences using one_ffluency.

1	ffluency(adjlist, n, pjump = 0, type = 0L, string = FALSE)

`adjlist`	a list containing row indices of nodes adjacent node to the ith node as created by get_adjlist.
`n`	integer vector specifying for each sequence the maximum numbers of productions. Function may return fewer than `n`.
`pjump`	numeric specifying the probability of a jump.
`type`	integer controlling network start and jump nodes. For `type = 0` the process selects the start node and any jump nodes proportional to their degree. For `type = 1` the process selects a random node to serve both as the start node and the jump node. For `type = 2` the process selects the start and any jump nodes uniformly at random.
`string`	logical specifying whether the output should be of mode character.

For details see one_ffluency.

List of character vectors containing the indices of the fluency productions. Indices refer to the row of the item in the original adjacency matrix. See get_adjlist.

Wulff, D. U., Hills, T., & Mata, R. (2018, October 29). Structural differences in the semantic networks of younger and older adults. https://doi.org/10.31234/osf.io/s73dp

Goni, J., Martincorena, I., Corominas-Murtra, B., Arrondo, G., Ardanza- Trevijano, S., & Villoslada, P. (2010). Switcher-random-walks: A cognitive- inspired mechanism for network exploration. International Journal of Bifurcation and Chaos, 20(03), 913-922.

# generate watts strogatz graph
network = grow_ws(n = 100, k = 10)

# create verbal fluency sequences
ffluency(get_adjlist(network), c(10, 10))

# create verbal fluency sequence
# with high jump probability
ffluency(get_adjlist(network), c(10, 10), pjump = .5)