Package: hgwrr 0.6-0

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_0.6-0.tar.gz
hgwrr_0.6-0.zip(r-4.5)hgwrr_0.6-0.zip(r-4.4)hgwrr_0.6-0.zip(r-4.3)
hgwrr_0.6-0.tgz(r-4.4-x86_64)hgwrr_0.6-0.tgz(r-4.4-arm64)hgwrr_0.6-0.tgz(r-4.3-x86_64)hgwrr_0.6-0.tgz(r-4.3-arm64)
hgwrr_0.6-0.tar.gz(r-4.5-noble)hgwrr_0.6-0.tar.gz(r-4.4-noble)
hgwrr_0.6-0.tgz(r-4.4-emscripten)hgwrr_0.6-0.tgz(r-4.3-emscripten)
hgwrr.pdf |hgwrr.html✨
hgwrr/json (API)
NEWS

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

Peer review:

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

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:

4.85 score 1 stars 6 scripts 351 downloads 6 exports 14 dependencies

Last updated 5 days agofrom:a9f8a4cfea. Checks:OK: 3 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-win-x86_64OKNov 15 2024
R-4.5-linux-x86_64OKNov 15 2024
R-4.4-win-x86_64NOTENov 15 2024
R-4.4-mac-x86_64NOTENov 15 2024
R-4.4-mac-aarch64NOTENov 15 2024
R-4.3-win-x86_64NOTENov 15 2024
R-4.3-mac-x86_64NOTENov 15 2024
R-4.3-mac-aarch64NOTENov 15 2024

Exports:hgwrhgwr_fitmake_dummymake_dummy_extractspatial_hetero_testspatial_hetero_test_data

Dependencies:classclassIntDBIe1071KernSmoothmagrittrMASSproxyRcppRcppArmadillos2sfunitswk

hgwrr

Rendered fromhgwrr.Rmdusingknitr::rmarkdownon Nov 15 2024.

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

Readme and manuals

Help Manual

Help pageTopics
HGWR: Hierarchical and Geographically Weighted Regressionhgwrr-package
Get estimated coefficients.coef.hgwrm
Get fitted response.fitted.hgwrm
Log likelihood functionlogLik.hgwrm
Make Dummy Variablesmake_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 testprint.spahetbootres
Print summary of an 'hgwrm' object.print.summary.hgwrm
Get residuals.residuals.hgwrm
Generic method to test spatial heterogeneityspatial_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 Regressionhgwr 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