R Observatory: Metrics for SpatialInference version 0.1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

SpatialInference

0.1.0Package record

Tools for Statistical Inference with Geo-Coded Data

0packages depend

1.5Kdownloads / year

48.5%test coverage

13/13flavors OK

Overview

About

Maintained by Alexander LehnerCRAN page ↗GitHub ↗Issues ↗

Fast computation of Conley (1999) doi:10.1016/S0304-4076(98)00084-0 spatial heteroskedasticity and autocorrelation consistent (HAC) standard errors for linear regression models with geo-coded data, with a fast C++ implementation by Christensen, Hartman, and Samii (2021) doi:10.1017/S0020818321000187. Performance-critical distance calculations, kernel weighting, and variance component accumulation are implemented in C++ via 'Rcpp' and 'RcppArmadillo'. Includes tools for estimating the spatial correlation range from covariograms and correlograms following the bandwidth selection method proposed in Lehner (2026) doi:10.48550/arXiv.2603.03997, and diagnostic visualizations for bandwidth selection.

Changes in 0.1.0

Initial CRAN release.

Conley spatial HAC standard errors

conley_SE() computes Conley (1999) spatial HAC variance-covariance matrices for lfe::felm() models, with support for cross-sectional spatial correlation, serial (temporal) correlation, and the combined spatial HAC estimator.
Six kernel functions: Bartlett, Epanechnikov, Gaussian, Parzen, Biweight, and Uniform.
Haversine great-circle distances (default) and a 111 km/degree approximation.
Balanced-panel optimisation pre-computes the distance matrix once.
compute_conley_lfe() convenience wrapper for quick single-coefficient extraction.
lm_sac() all-in-one workflow: regression, Moran's I tests, and Conley standard errors, with modelsummary integration via custom tidy and glance methods.

Show all changes in 0.1.0Hide the rest of the changes in 0.1.0

Bandwidth selection

covgm_range() estimates the spatial correlation range from the empirical covariogram of regression residuals (Lehner 2026).
extract_corr_range() extracts the zero-crossing distance from a covariogram (gstat::variogram()) or correlogram (ncf::correlog()).
inverseu_plot_conleyrange() diagnostic plot showing how the Conley SE varies with the bandwidth, revealing the inverse-U relationship (Lehner 2026).

Spatial utilities

DistMat() kernel-weighted spatial distance matrix (C++).
coords_as_columns() extracts sf point coordinates into tibble columns.
gravity_centroid() computes the (optionally weighted) geographic centroid of an sf object.
grid_FE() assigns observations to spatial grid cells for use as fixed effects.

Performance

Distance matrix computation, kernel weighting, and variance component accumulation (XeeXhC, Bal_XeeXhC, XeeXhC_Lg, TimeDist) are implemented in C++ via Rcpp and RcppArmadillo.
Memory-efficient large-sample variant (XeeXhC_Lg) avoids constructing the full n x n distance matrix when n > 50,000.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("SpatialInference", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("axlehner/SpatialInference")

Development version from axlehner/SpatialInference. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-spatialinference

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-SpatialInference

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-SpatialInference

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 3.5 min · r-devel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-04-22
ERROR12 OK, 1 ERROR2026-04-18
OK5 OK2026-03-26

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.1.0

READMEYes · 315 wordsVignettesYes · 1 · dynamicNEWSYes · 67% structured · mentions 0.1.0Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 21 (6 internal)includes a package overview page
Examples that run: 11%1 run in a plain check · 8 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 60%
Documented parameters: 100%
Return-value docs: 93%
Help pages citing references: 48%

Vignettes (1)

spatial_HAC HTML

How these are measured

Downloads

1.5K

CRAN downloads in the past year

Rank #22,026 · ~4/day · ~125/mo

Releases R versions

Daily download trend is not available in this view yet.

19830 days

60190 days

1.5K1 year

Compare downloads with other packages →

Also on171 r2u2 autocran

How downloads are counted

Repository

axlehner/spatialinference ↗Account: axlehner

2Stars

0Forks

0Open issues

0Open PRs

0Releases

57Commits

2Commit identities

License file reads as GPL-3.0 · 57 commits · Last activity 2026-03-21 · +100% stars, 30d

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: not measured
Median days to close, 50 most recently updated closed PRs: 0

Stars over time

2026-07-07 · 02026-10-22 · 2

How these are measured

PracticesBeta

3 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/axlehner/spatialinference on 2026-10-18.

Continuous integration (1)

GitHub Actions

CRAN release process (1)

cran-comments.md

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

21 external dependencies (excludes base and recommended)

Installing SpatialInference adds 21 packages (17 with compiled code, 27 MB of source tarballs). Heaviest: sf 9.3 MB, data.table 5.7 MB, s2 2.8 MB.

Depends (1)

R >= 4.1.0

Imports (6)

Rcpp sf data.table magrittrstatstibble

LinkingTo (2)

Rcpp RcppArmadillo

Suggests (14)

lfe fixest dplyr stringr spdep ncf gstat sandwich ggplot2 modelsummary knitr rmarkdown geosphere testthat

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (1)

Alexander Lehner

Author, Maintainer since 0.1.0 (2026)

Releases (1)

R
R 4.6.0 released · 2026-04-24
0.1.0Latest
record
2026-03-25 · current release
R
R 4.5.0 released · 2025-04-11

Package metadata

First published: 2026-03-25
Total releases: 1 / 1 yrs
License: GPL (>= 3) OSI
Minimum R: ≥ 4.1.0
Bundled data: 439 KB / 1 file
Download size: 1.1 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SpatialInference")

Format

Lehner, A. (2026). SpatialInference: Tools for Statistical Inference with Geo-Coded Data (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.SpatialInference

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SpatialInference version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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