Package: hgwrr 0.6-2

hgwrr: Hierarchical and Geographically Weighted Regression

This model divides coefficients into three types, i.e., local fixed effects, global fixed effects, and random effects (Hu et al., 2022)<doi:10.1177/23998083211063885>. If data have spatial hierarchical structures (especially are overlapping on some locations), it is worth trying this model to reach better fitness.

Authors:Yigong Hu [aut, cre], Richard Harris [aut], Richard Timmerman [aut]

hgwrr_0.6-2.tar.gz
hgwrr_0.6-2.zip(r-4.7)hgwrr_0.6-2.zip(r-4.6)hgwrr_0.6-2.zip(r-4.5)
hgwrr_0.6-2.tgz(r-4.6-x86_64)hgwrr_0.6-2.tgz(r-4.6-arm64)hgwrr_0.6-2.tgz(r-4.5-x86_64)hgwrr_0.6-2.tgz(r-4.5-arm64)
hgwrr_0.6-2.tar.gz(r-4.7-arm64)hgwrr_0.6-2.tar.gz(r-4.7-x86_64)hgwrr_0.6-2.tar.gz(r-4.6-arm64)hgwrr_0.6-2.tar.gz(r-4.6-x86_64)
hgwrr_0.6-2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
hgwrr/json (API)

# Install 'hgwrr' in R:

install.packages('hgwrr', repos = c('https://hpdell.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/hpdell/hgwrr/issues

Pkgdown/docs site:https://hpdell.github.io

Uses libs:

openblas– Optimized BLAS
gsl– GNU Scientific Library (GSL)
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

mulsam.test - Simulated Spatial Multisampling Data For Test
multisampling - Large Scale Simulated Spatial Multisampling Data
wuhan.hp - Wuhan Second-hand House Price and POI Data

On CRAN:

openblas gsl cpp openmp

4.18 score 3 stars 7 scripts 321 downloads 6 exports 13 dependencies

Last updated from:27376766a9. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	206
linux-devel-x86_64	OK	248
source / vignettes	OK	246
linux-release-arm64	OK	203
linux-release-x86_64	OK	200
macos-release-arm64	OK	195
macos-release-x86_64	OK	612
macos-oldrel-arm64	OK	216
macos-oldrel-x86_64	OK	368
windows-devel	OK	230
windows-release	OK	207
windows-oldrel	OK	298
wasm-release	OK	142

Exports:hgwr hgwr_fit make_dummy make_dummy_extract spatial_hetero_test spatial_hetero_test_data

Dependencies:class classInt DBI e1071 KernSmooth MASS proxy Rcpp RcppArmadillo s2 sf units wk

hgwrr

Rendered fromhgwrr.Rmdusingknitr::rmarkdown

Last update: 2024-10-16
Started: 2024-06-18

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
HGWR: Hierarchical and Geographically Weighted Regression	hgwrr-package
Get estimated coefficients.	coef.hgwrm
Get fitted response.	fitted.hgwrm
Log likelihood function	logLik.hgwrm
Make Dummy Variables	make_dummy make_dummy_extract make_dummy_extract.character make_dummy_extract.default make_dummy_extract.factor make_dummy_extract.logical
Simulated Spatial Multisampling Data For Test (DataFrame)	mulsam.test
Large Scale Simulated Spatial Multisampling Data (DataFrame)	multisampling
Print a character matrix as a table.	print_table_md
Print description of a 'hgwrm' object.	print.hgwrm
Print the result of spatial heterogeneity test	print.spahetbootres
Print summary of an 'hgwrm' object.	print.summary.hgwrm
Get residuals.	residuals.hgwrm
Generic method to test spatial heterogeneity	spatial_hetero_test spatial_hetero_test.data.frame spatial_hetero_test.default spatial_hetero_test.matrix spatial_hetero_test.numeric spatial_hetero_test.sf spatial_hetero_test.vector
Test the spatial heterogeneity in data based on permutation.	spatial_hetero_test_data
Hierarchical and Geographically Weighted Regression	hgwr hgwr.data.frame hgwr.sf hgwr_fit spatial_hetero_test.hgwrm
Summary an 'hgwrm' object.	summary.hgwrm
Wuhan Second-hand House Price and POI Data (DataFrame)	wuhan.hp