| Title: | Information Consistency-Based Measures for Spatial Stratified Heterogeneity |
| Version: | 0.1.0 |
| Description: | Spatial stratified heterogeneity (SSH) denotes the coexistence of within-strata homogeneity and between-strata heterogeneity. Information consistency-based methods provide a rigorous approach to quantify SSH and evaluate its role in spatial processes, grounded in principles of geographical stratification and information theory (Bai, H. et al. (2023) <doi:10.1080/24694452.2023.2223700>; Wang, J. et al. (2024) <doi:10.1080/24694452.2023.2289982>). |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| URL: | https://stscl.github.io/sshicm/, https://github.com/stscl/sshicm |
| BugReports: | https://github.com/stscl/sshicm/issues |
| Depends: | R (≥ 4.1.0) |
| LinkingTo: | Rcpp, RcppThread |
| Imports: | dplyr, purrr, sdsfun (≥ 0.5.0), sf |
| Suggests: | gdverse, knitr, rmarkdown |
| VignetteBuilder: | knitr |
| NeedsCompilation: | yes |
| Packaged: | 2024-12-02 16:04:56 UTC; dell |
| Author: | Wenbo Lv  [aut,
cre, cph] |
| Maintainer: | Wenbo Lv <lyu.geosocial@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2024-12-03 19:00:02 UTC |
Measurement of Spatial Stratified Heterogeneity Based on Information Consistency for Continuous Variables
Description
Measurement of Spatial Stratified Heterogeneity Based on Information Consistency for Continuous Variables
Usage
sshic(d, s, seed = 42, permutation_number = 999, bin_method = "Sturges")
Arguments
d |
The target variable. |
s |
The stratification. |
seed |
(optional) Random number seed, default is |
permutation_number |
(optional) Number of Random Permutations, default is |
bin_method |
(optional) Histogram binning method for probability density estimation, default is
|
Value
A two-element numerical vector.
Examples
# This code may take a bit longer to execute:
baltim = sf::read_sf(system.file("extdata/baltim.gpkg",package = "sshicm"))
sshic(baltim$PRICE,baltim$DWELL)
Information Consistency-Based Measures for Spatial Stratified Heterogeneity
Description
Information Consistency-Based Measures for Spatial Stratified Heterogeneity
Usage
sshicm(
formula,
data,
type = "IC",
seed = 42,
permutation_number = 999,
bin_method = "Sturges"
)
Arguments
formula |
A formula. |
data |
A |
type |
(optional) Measure type, default is |
seed |
(optional) Random number seed, default is |
permutation_number |
(optional) Number of Random Permutations, default is |
bin_method |
(optional) Histogram binning method for probability density estimation, default is
|
Value
A tibble.
Examples
# This code may take a bit longer to execute:
baltim = sf::read_sf(system.file("extdata/baltim.gpkg",package = "sshicm"))
sshicm(PRICE ~ .,baltim,type = "IC")
cinc = sf::read_sf(system.file("extdata/cinc.gpkg",package = "sshicm"))
sshicm(THEFT_D ~ .,cinc,type = "IN")
Measurement of Spatial Stratified Heterogeneity Based on Information Consistency for Nominal Variables
Description
Measurement of Spatial Stratified Heterogeneity Based on Information Consistency for Nominal Variables
Usage
sshin(d, s, seed = 42, permutation_number = 999)
Arguments
d |
The target variable. |
s |
The stratification. |
seed |
(optional) Random number seed, default is |
permutation_number |
(optional) Number of Random Permutations, default is |
Value
A two-element numerical vector.
Examples
# This code may take a bit longer to execute:
cinc = sf::read_sf(system.file("extdata/cinc.gpkg",package = "sshicm"))
sshin(cinc$THEFT_D,cinc$MALE)