joincount.mc: Permutation test for same colour join count statistics

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

View source: R/jc.R

Description

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.

Usage

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

Arguments

fx

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

listw

a listw object created for example by nb2listw

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 get.spChkOption()

Value

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

Author(s)

Roger Bivand [email protected]

References

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

See Also

joincount.test

Examples

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data(oldcol)
HICRIME <- cut(COL.OLD$CRIME, breaks=c(0,35,80), labels=c("low","high"))
names(HICRIME) <- rownames(COL.OLD)
joincount.mc(HICRIME, nb2listw(COL.nb, style="B"), nsim=99)
joincount.test(HICRIME, nb2listw(COL.nb, style="B"))

Example output

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.