spqdep (version 0.1.3.6)

m.surround: A function to generate m-surroundings

Description

This function obtains the m-surroundings by selecting the m-1 nearest neighbors of each observation, allowing for a degree of overlap of r.

Usage

m.surround(x, m, r = 1, distance = "Euclidean", control = list())

Value

A list of class list and m_surr containing the following components:

ms	a matrix. Each row is a m-surrounding.
R	total number of observations.
rowexcl	index of rows excluded.
mdtms	distances between the observations of each m-surrounding.
N	total number of symbolized observations.
m	length of the m-surroundings.
r	overlapping degree.
initobs	element to start the generation of m-surroundings.
distance	type of distance.
m	length of the m-surroundings.
x	the input "x" as sf-object.

Arguments

x

input sf object with points/multipolygons geometry or matrix of spatial coordinates

m

dimension of m-surrounding

r

maximum overlapping between any two m-surroundings.

distance

character. For Cartesian coordinates only: one of Euclidean, Hausdorff or Frechet; for geodetic coordinates, Great Circle distances are computed. (see sf::st_distance()). Default = "Euclidean".

control

List of additional control arguments.

Control arguments

• initobs: Initial observation to begin the m-surrounding process. Default = 1.

• dtmaxabs: Threshold of distance (in absolute value) to prune the m-surroundings. Any m-surrounding exceeding the threshold is excluded. If dtmaxabs = 0 there is no exclusion of m-surroundings. Default = 0.

• dtmaxpc: Threshold of distance (as a percentage of the maximum distance between observations) to prune the m-surroundings. Any m-surrounding exceeding the threshold is excluded. Example if dtmaxpc = 0.1 the m-surrounding exceeding the 10% of the maximum distance between observations are excluded. If dtmaxpc = 0 there is no exclusion of m-surroundings. Default = 0.

• dtmaxknn: Eliminate m-surroundings where some of the elements are not among the closest knn (k-nearest-neighbors). Example, if dtmaxknn = 4 exclude m-surroundings where some of the elements are not between the 4 closest. Default dtmaxknn = 0 (no exclusion)

Author

Fernando López
Román Mínguez
Antonio Páez
Manuel Ruiz

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

# Example 1: Obtain m-surroundings with degree of overlapping r
N <- 100
cx <- runif(N)
cy <- runif(N)
x <- cbind(cx,cy)
m <- 3
r <- 1
msurr_points <- m.surround(x = x, m = m, r = r)
plot(msurr_points, type = 1)
plot(msurr_points, type = 2)
summary(msurr_points)
msurr_points <- m.surround(x = x, m = m, r = r,
                control = list(dtmaxpc = 0.1))
plot(msurr_points, type = 1)
plot(msurr_points, type = 2)
summary(msurr_points)
msurr_points <- m.surround(x = x, m = m, r = r,
                   control = list(dtmaxknn = 20))
plot(msurr_points, type = 1)
plot(msurr_points, type = 2)
summary(msurr_points)

# Example 2:
# \donttest{
data("FastFood.sf")
m <- 3
r <- 1
msurr_points <- m.surround(x = FastFood.sf, m = m, r = r,
                           distance = "Euclidean",
                           control = list(dtmaxpc = .001))
plot(msurr_points, type = 1)
plot(msurr_points, type = 2)
print(msurr_points)
summary(msurr_points)
msurr_points <- m.surround(x = FastFood.sf, m = m, r = r,
                           distance = "Euclidean",
                           control = list(dtmaxknn = 20))
plot(msurr_points, type = 1)
plot(msurr_points, type = 2)
summary(msurr_points)
# }

# Example 3: With isolated areas
data(provinces_spain)
# sf::sf_use_s2(FALSE)
plot(sf::st_geometry(provinces_spain))
m <- 3
r <- 1
msurr_points <- m.surround(x = provinces_spain, m = m, r = r,
                           distance = "Euclidean",
                           control = list(dtmaxknn = 8))
plot(msurr_points, type = 1)
plot(msurr_points, type = 2)

# Example 4: With regular lattice
sfc = sf::st_sfc(sf::st_polygon(list(rbind(c(0,0), c(1,0), c(1,1), c(0,1), c(0,0)))))
hexs <- sf::st_make_grid(sfc, cellsize = 0.1, square = FALSE)
hexs.sf <- sf::st_sf(hexs)
listw  <- spdep::poly2nb(as(hexs.sf, "Spatial"), queen = FALSE)
m <- 3
r <- 1
msurr_polygonsf <- m.surround(x = hexs.sf, m = m, r = r)
plot(msurr_polygonsf, type = 1)
plot(msurr_polygonsf, type = 2)
summary(msurr_polygonsf)