Description Usage Arguments Details Value References Examples

Generates verbal fluency data using a switcher-random walk process.

1 | ```
one_ffluency(adj_list, n, pjump = 0, type = 0L)
``` |

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

`n` |
integer specifying the maximum number of productions. Function may
return fewer than |

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

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

Function produces verbal fluency data via a switcher random walk
process that traverses the network by selecting a neighbor with
probability `1-pjump`

or jumps to a random place in the network
with probability `pjump`

. Where the random walk process enters
the network and where it jumps to is further controlled
by `type`

. Neighbors are always selected uniformly.

In contrast to fluency, this function does not check at every step
whether the sampled neighbor is already in the list of productions. Instead,
`ffluency`

simply returns the list of unique productions. This means
that if repetitions occur `ffluency`

will produce sequences of length
`min(n * 3 - k, n)`

where k is the number of repeptitions.

Integer vector 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)
# create verbal fluency sequences
one_ffluency(get_adjlist(network), 10)
# create verbal fluency sequence
# with high jump probability
one_ffluency(get_adjlist(network), 10, pjump = .5)
``` |

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