Description Usage Arguments Details Value References Examples

Repeatedly generates verbal fluency data using one_fluency_steps and
counts the number of steps required to produce `n`

unique responses.

1 | ```
fluency_steps(adjlist, n, pjump = 0, type = 0L)
``` |

`adjlist` |
a list containing row indices of nodes adjacent node to the ith node as created by get_adjlist. |

`n` |
integer vector specifying the numbers of production. |

`pjump` |
numeric specifying the probability of a jump. |

`type` |
integer controlling network start and jump nodes.
For |

For details see one_fluency_steps.

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.

1 2 3 4 5 6 7 8 9 | ```
# generate watts strogatz graph
network = grow_ws(n = 100, k = 10)
# count number of steps needed to create sequence
fluency_steps(get_adjlist(network), c(10, 10))
# count number of steps needed to create sequence
# with high jump probability
fluency_steps(get_adjlist(network), c(10, 10), pjump = .5)
``` |

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