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spdep (version 1.3-6)

local_joincount_bv: Calculate the local bivariate join count

Description

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

Usage

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

Value

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

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".

Author

Josiah Parry josiah.parry@gmail.com

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.

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")

Examples

Run this code
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)

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