iterate_kp | R Documentation |

Iterating a kp network

iterate_kp(adjm, np, pb, k, p) ## S4 method for signature 'matrix,numeric,numeric,numeric,numeric' iterate_kp(adjm, np, pb, k, p)

`adjm` |
Adjacency matrix |

`np` |
numeric vector setting ids for the newborn (i.e. which individual will be replaced with a new one) and a parent(s). Length 2 or 3. If you want to randomly select an id for the newborn (first value) and parents (second and third value), simply use c(0,0) or c(0,0,0). For one parent, the focal individual connects to this parent with probability pb. For two parent values, the individual connects to two parents each with probability pb. |

`pb` |
Probability to connect to parent. Default is 1. |

`k` |
Degree (number of connections a new individual will form) |

`p` |
Maximum proportion of k that will be connections to neighbours of the parent. The complimentary k*(1-p) connections will be formed with random other individuals |

If you just want to iterate the graph you can use `np=c(0,0)`

or `np=c(0,0,0)`

. However, the function does not return the ids of the newborn and the parent(s). If you want to keep track of the ids that are changed, you should provide these as an input to the function.

Returns an iterated version of the supplied adjacency matrix as a numeric matrix.

# Set up linking parameters: pb <- 1 k <- 4 p <- 0.2 # Generate a network based on these parameters adjm_t0 <- make_kp(n = 100, np=c(0,0), pb = pb, k = k, p = p) # Iterate the network adjm_t1 <- iterate_kp(adjm = adjm_t0, np=c(0,0), pb = pb, k = k, p = p)

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