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estimateW

0.2.0Package record

Estimation of Spatial Weight Matrices

0packages depend
4.3Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Bayesian estimation of spatial weight matrices in spatial econometric panel models. Allows for estimation of spatial autoregressive (SAR), spatial error (SEM), spatial Durbin (SDM), spatial error Durbin (SDEM) and spatially lagged explanatory variable (SLX) type specifications featuring an unknown spatial weight matrix. Methodological details are given in Krisztin and Piribauer (2022) doi:10.1080/17421772.2022.2095426.

Changes in 0.2.0
  • Added slx() function for estimating Spatial Lag of X (SLX) models with exogenous spatial weight matrices.
  • Added logdetSpline() function implementing spline-based approximations for the log-determinant in rho sampling.
  • Updated default rho prior to utilize the Pace and Barry approximation for improved computational efficiency.
  • Fixed bug where print and plot methods failed to correctly handle SEM and SLX model objects.
  • Corrected temporal indices in the NUTS1 growth dataset.
  • Optimized posterior sampling routines for improved convergence in high-dimensional settings.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 1.5 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.2.0
READMEYes · 94 wordsVignettesNoNEWSYes · 100% structured · mentions 0.2.0Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
29
Examples that run
100%12 run in a plain check
Exported functions with examples
48%
Documented parameters
87%
Return-value docs
48%
Help pages citing references
28%

Downloads

4.3K
CRAN downloads in the past year
Rank #9,549 · ~12/day · ~361/mo
Daily download trend is not available in this view yet.
36530 days
1K90 days
4.3K1 year
Compare downloads with other packages →
Also on79 r2u6 autocran

Dependencies

Declared dependencies
3 external dependencies (excludes base and recommended)

Installing estimateW adds 3 packages (0 with compiled code, 2.8 MB of source tarballs). Heaviest: plot.matrix 2.7 MB, R6 63 KB, matrixcalc 30 KB.

Depends (1)
R >= 3.5.0
Imports (7)
graphicsMatrixmatrixcalcplot.matrixR6statsutils
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (2)
Author, Maintainer since 0.0.1 (2022)
Releases (3)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.2.0Latest
    record
    2026-03-13 · current release · diff ↗ ·
    added 2 exports
    logdetSpline, slx
  • 0.1.0
    record
    2025-05-13 · diff ↗ ·
    added 4 exports
    sdem, sdemw, sem, semw
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • 0.0.1
    record
    2022-12-06
  • R
    R 4.2.0 released · 2022-04-22

Package metadata

First published
2022-12-06
Total releases
3 / 4 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 3.5.0
Bundled data
42 KB / 2 files
Download size
85 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("estimateW")
Krisztin, T., & Piribauer, P. (2026). estimateW: Estimation of Spatial Weight Matrices (Version 0.2.0) [Computer software]. https://doi.org/10.32614/CRAN.package.estimateW

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.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for estimateW version 0.2.0 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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