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Title:

A Correlation Indicator Based on Spatial Patterns

Version:

0.2.0

Description:

Utilizes spatial association marginal contributions derived from spatial stratified heterogeneity to capture the degree of correlation between spatial patterns.

License:

GPL-3

Encoding:

UTF-8

RoxygenNote:

7.3.3

URL:

https://stscl.github.io/cisp/, https://github.com/stscl/cisp

BugReports:

https://github.com/stscl/cisp/issues

Depends:

R (≥ 4.1.0)

Imports:

dplyr, forcats, gdverse (≥ 1.5), ggplot2, ggraph, igraph, magrittr, parallel, purrr, sdsfun (≥ 0.7.0), sf, tibble, tidyr

Suggests:

knitr, rmarkdown, spEDM

VignetteBuilder:

knitr

NeedsCompilation:

Packaged:

2026-02-07 05:06:22 UTC; dell

Author:

Wenbo Lv

[aut, cre, cph], Yongze Song

[aut], Rui Qu

[aut], Wufan Zhao

[aut], Nan Jia

[aut]

Maintainer:

Wenbo Lv <lyu.geosocial@gmail.com>

Repository:

CRAN

Date/Publication:

2026-02-07 06:11:02 UTC

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Value

NULL (this is the magrittr pipe operator)

spatial pattern correlation

Description

spatial pattern correlation

Usage

spc(
  data,
  overlay = "and",
  discnum = 3:8,
  discmethod = c("sd", "equal", "geometric", "quantile", "natural"),
  cores = 1
)

Arguments

data

A data.frame, tibble or sf object of observation data.

overlay

(optional) Spatial overlay method. One of and, or, intersection. Default is and.

discnum

(optional) A vector of number of classes for discretization. Default is 3:8.

discmethod

(optional) A vector of methods for discretization, default is using c("sd","equal","geometric","quantile","natural") by invoking sdsfun.

cores

(optional) Positive integer (default is 1). When cores are greater than 1, use parallel computing.

Value

A list.

cor_tbl: A tibble with power of spatial pattern correlation
cor_mat: A matrix with power of spatial pattern correlation

Examples

sim1 = sf::st_as_sf(gdverse::sim,coords = c('lo','la'))
sim1

g = spc(sim1, discnum = 3:6, cores = 1)
g
plot(g,"matrix")

spatial association marginal contributions derived from spatial stratified heterogeneity

Description

spatial association marginal contributions derived from spatial stratified heterogeneity

Usage

ssh_marginalcontri(formula, data, overlay = "and", cores = 1)

Arguments

formula

A formula of ISP model.

data

A data.frame, tibble or sf object of observation data.

overlay

(optional) Spatial overlay method. One of and, or, intersection. Default is and.

cores

(optional) Positive integer (default is 1). When cores are greater than 1, use parallel computing.

Value

A list.

pd: power of determinants
spd: shap power of determinants
determination: determination of the optimal interaction of variables

Examples

NTDs1 = sf::st_as_sf(gdverse::NTDs, coords = c('X','Y'))
g = ssh_marginalcontri(incidence ~ ., data = NTDs1, cores = 1)
g
plot(g)