Q.test: A function to compute q test for spatial qualitative data...

In rominsal/spqdata: Testing for spatial structure of qualitative data in cross section

Description

A function to compute Q test for spatial qualitative data

Usage

Q.test(formula = NULL, data = NULL, na.action,
m = 3, r = 1, distr = "asymptotic",
xf = NULL, coor = NULL, control = list())

Arguments

formula	a symbolic description of the factor(s).
data	an (optional) data frame or a sf object containing the variable to testing for.
xf	input sf object with points/multipolygons geometry or matrix of spatial coordinates.
coor	(optional) a 2xN vector with coordinates
m	length of m-surrounding (default = 3).
r	maximum overlapping between any two m-surroundings (default = 1).
distr	character. Distribution type "asymptotic" (default) or "bootstrap".
control	Optional argument. See Control Argument section.

Details

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Value

An object of the class htest #'

Control arguments

distance

character to select the type of distance. Default = "Euclidean" for Cartesian coordinates only: one of Euclidean, Hausdorff or Frechet; for geodetic coordinates, great circle distances are computed (see sf::st_distance())

dtmaxabs

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dtmaxpc

Elimina m-surrounding

nsim

number of boots for get the bootstrap distribution. Default = 999

seedinit

seed to select the initial element to star the algorithm to get compute the m-surroundings or to start the bootstrap

Author(s)

Fernando López	[e-mail]
Román Mínguez	[e-mail]
Antonio Páez	[e-mail]
Manuel Ruiz	[e-mail]

References

• Ruiz M, López FA, A Páez. (2010). Testing for spatial association of qualitative data using symbolic dynamics. Journal of Geographical Systems. 12 (3) 281-309

Examples

Case 1: With coordinates
rm(list = ls())
N <- 100
cx <- runif(N)
cy <- runif(N)
coor <- cbind(cx,cy)
p <- c(1/6,3/6,2/6)
rho = 0.5
listw <- spdep::nb2listw(knn2nb(knearneigh(cbind(cx,cy), k = 4)))
xf <- dgp.spq(list = listw, p = p, rho = rho)
q.test <- Q.test(xf = xf, coor = coor, m = 3, r = 1)
summary(q.test)
plot(q.test)
print(q.test)
q.test.boot <- Q.test(xf = xf, coor = coor, m = 3, r = 1, distr = "bootstrap")
summary(q.test.boot)
plot(q.test)
print(q.test)

Case 2: With a sf object
rm(list = ls())
data("FastFood")
f1 <- ~ Type
q.test <- Q.test(formula = f1, data = FastFood.sf, m = 3, r = 1, control = list(distance ="Euclidean"))
summary(q.test)
plot(q.test)
print(q.test)
# Case 3: With a sf object with isolated areas
rm(list = ls())
data("Spain")
f1 <- ~ MenWoman
q.test <- Q.test(formula = f1, data = spain.sf, m = 3, r = 1, control = list(seedinit = 1111))
summary(q.test)
print(q.test)
plot(q.test)
q.test.boot <- Q.test(formula = f1, data = spain.sf, m = 4, r = 3, distr = "bootstrap", control = list(seedinit = 1111))
summary(q.test.boot)
print(q.test.boot)
plot(q.test.boot)
# Case 4: Examples with multipolygons
rm(list = ls())
library(sf)
fname <- system.file("shape/nc.shp", package="sf")
nc <- st_read(fname)
qb79 <- quantile(nc$BIR79)
nc$QBIR79 <- (nc$BIR79 > qb79[2]) + (nc$BIR79 > qb79[3]) +
(nc$BIR79 >= qb79[4]) + 1
nc$QBIR79 <- as.factor(nc$QBIR79)
plot(nc["QBIR79"], pal = c("#FFFEDE","#FFDFA2", "#FFA93F", "#D5610D"),
     main = "BIR79 (Quartiles)")
sid79 <- quantile(nc$SID79)
nc$QSID79 <- (nc$SID79 > sid79[2]) + (nc$SID79 > sid79[3]) +
(nc$SID79 >= sid79[4]) + 1
nc$QSID79 <- as.factor(nc$QSID79)
plot(nc["QSID79"], pal = c("#FFFEDE","#FFDFA2", "#FFA93F", "#D5610D"),
     main = "SID79 (Quartiles)")
f1 <- ~ QSID79 + QBIR79
lq1nc <- Q.test(formula = f1, data = nc, m = 5, r = 2,
control = list(seedinit = 1111, dtmaxpc = 0.5, distance = "Euclidean") )
print(lq1nc)

lq2nc <- Q.test(formula = f1, data = nc, m = 5, r = 2, control = list(dtmaxpc = 0.2) )
print(lq2nc)

lq3nc <- Q.test(formula = f1, data = nc, m = 5, r = 2, control = list(dtmaxknn = 5) )
print(lq3nc)

# Case 5: Examples with points and matrix of variables
xf <- matrix(c(nc$QBIR79, nc$QSID79), ncol = 2, byrow = TRUE)
mctr <- suppressWarnings(sf::st_centroid(sf::st_geometry(nc)))
mcoor <- sf::st_coordinates(mctr)[,c("X","Y")]
q.test <- Q.test(xf = xf, coor = mcoor, m = 5, r = 2,control = list(seedinit = 1111, dtmaxpc = 0.5))
print(q.test)
plot(q.test)

rominsal/spqdata documentation built on Jan. 24, 2021, 11:11 a.m.