local_joincount_bv function

Calculate the local bivariate join count

The bivariate join count (BJC) evaluates event occurrences in predefined regions and tests if the co-occurrence of events deviates from complete spatial randomness.

local_joincount_bv(
  x,
  z,
  listw,
  nsim = 199,
  alternative = "two.sided"
)

Arguments

• x: a binary variable either numeric or logical
• z: a binary variable either numeric or logical with the same length as x
• listw: a listw object containing binary weights created, for example, with nb2listw(nb, style = "B")
• nsim: the number of conditional permutation simulations
• alternative: default "greater". One of "less" or "greater".

Details

There are two cases that are evaluated in the bivariate join count. The first being in-situ colocation (CLC) where xi = 1 and zi = 1. The second is the general form of the bivariate join count (BJC) that is used when there is no in-situ colocation.

The BJC case "is useful when x and z cannot occur in the same location, such as when x and z correspond to two different values of a single categorical variable" or "when x and z can co-locate, but do not" (Anselin and Li, 2019). Whereas the CLC case is useful in evaluating simultaneous occurrences of events.

The local bivariate join count statistic requires a binary weights list which can be generated with nb2listw(nb, style = "B").

P-values are only reported for those regions that match the CLC or BJC criteria. Others will not have an associated p-value.

P-values are estimated using a conditional permutation approach. This creates a reference distribution from which the observed statistic is compared.

Returns

a data.frame with two columns join_count and p_sim and number of rows equal to the length of arguments x.

References

Anselin, L., & Li, X. (2019). Operational Local Join Count Statistics for Cluster Detection. Journal of geographical systems, 21(2), 189–210. tools:::Rd_expr_doi("10.1007/s10109-019-00299-x")

Author(s)

Josiah Parry josiah.parry@gmail.com

Examples

data("oldcol")
listw <- nb2listw(COL.nb, style = "B")
# Colocation case
x <- COL.OLD[["CP"]]
z <- COL.OLD[["EW"]]
set.seed(1)
res <- local_joincount_bv(x, z, listw)
na.omit(res)
# no colocation case
z <- 1 - x
set.seed(1)
res <- local_joincount_bv(x, z, listw)
na.omit(res)