Description Usage Arguments Value Author(s) References See Also Examples

A permutation test for same colour join count statistics calculated by using nsim random permutations of fx for the given spatial weighting scheme, to establish the ranks of the observed statistics (for each colour) in relation to the nsim simulated values.

1 2 | ```
joincount.mc(fx, listw, nsim, zero.policy=FALSE, alternative="greater",
spChk=NULL)
``` |

`fx` |
a factor of the same length as the neighbours and weights objects in listw |

`listw` |
a |

`nsim` |
number of permutations |

`zero.policy` |
if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA |

`alternative` |
a character string specifying the alternative hypothesis, must be one of "greater" (default), or "less". |

`spChk` |
should the data vector names be checked against the spatial objects for identity integrity, TRUE, or FALSE, default NULL to use |

A list with class `jclist`

of lists with class `htest`

and `mc.sim`

for each of the k colours containing the following components:

`statistic` |
the value of the observed statistic. |

`parameter` |
the rank of the observed statistic. |

`method` |
a character string giving the method used. |

`data.name` |
a character string giving the name(s) of the data. |

`p.value` |
the pseudo p-value of the test. |

`alternative` |
a character string describing the alternative hypothesis. |

`estimate` |
the mean and variance of the simulated distribution. |

`res` |
nsim simulated values of statistic, the final element is the observed statistic |

Roger Bivand [email protected]

Cliff, A. D., Ord, J. K. 1981 Spatial processes, Pion, p. 63-5.

1 2 3 4 5 |

```
Loading required package: sp
Loading required package: Matrix
Monte-Carlo simulation of join-count statistic
data: HICRIME
weights: nb2listw(COL.nb, style = "B")
number of simulations + 1: 100
Join-count statistic for low = 34, rank of observed statistic = 85,
p-value = 0.15
alternative hypothesis: greater
sample estimates:
mean of simulation variance of simulation
30.32323 18.58833
Monte-Carlo simulation of join-count statistic
data: HICRIME
weights: nb2listw(COL.nb, style = "B")
number of simulations + 1: 100
Join-count statistic for high = 54, rank of observed statistic = 100,
p-value = 0.01
alternative hypothesis: greater
sample estimates:
mean of simulation variance of simulation
27.02020 15.73428
Join count test under nonfree sampling
data: HICRIME
weights: nb2listw(COL.nb, style = "B")
Std. deviate for low = 1.0141, p-value = 0.1553
alternative hypothesis: greater
sample estimates:
Same colour statistic Expectation Variance
34.00000 29.59184 18.89550
Join count test under nonfree sampling
data: HICRIME
weights: nb2listw(COL.nb, style = "B")
Std. deviate for high = 6.3307, p-value = 1.22e-10
alternative hypothesis: greater
sample estimates:
Same colour statistic Expectation Variance
54.00000 27.22449 17.88838
```

spdep documentation built on Nov. 22, 2017, 5:07 p.m.

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