mlink.sim | R Documentation |

`mlink.test`

on simulated data`mlink.sim`

efficiently performs
`mlink.test`

on a simulated data set. The
function is meant to be used internally by the
`mlink.test`

function, but is informative for
better understanding the implementation of the test.

mlink.sim(nsim = 1, nn, ty, ex, w, pop, max_pop, cl = NULL)

`nsim` |
A positive integer indicating the number of simulations to perform. |

`nn` |
A list of distance-based nearest neighbors,
preferably from the |

`ty` |
The total number of cases in the study area. |

`ex` |
The expected number of cases for each region. The default is calculated under the constant risk hypothesis. |

`w` |
A binary spatial adjacency matrix for the regions. |

`pop` |
The population size associated with each region. |

`max_pop` |
The population upperbound (in total population) for a candidate zone. |

`cl` |
A cluster object created by |

A vector with the maximum test statistic for each simulated data set.

A vector with the maximum test statistic for each simulated data set.

data(nydf) data(nyw) coords <- with(nydf, cbind(longitude, latitude)) cases <- floor(nydf$cases) pop <- nydf$pop ty <- sum(cases) ex <- ty / sum(pop) * pop d <- sp::spDists(coords, longlat = TRUE) nn <- nndist(d, ubd = 0.05) max_pop <- sum(pop) * 0.25 tsim <- mlink.sim(1, nn, ty, ex, nyw, pop = pop, max_pop = max_pop )

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