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GWRLASSO

0.1.0

A Hybrid Model for Spatial Prediction Through Local Regression

0packages depend
2.1Kdownloads / year
0.0%test coverage
13/13checks pass

Overview

About
Maintained by Nobin Chandra PaulFirst published 2023-08-281 releasesCRAN page ↗

It implements a hybrid spatial model for improved spatial prediction by combining the variable selection capability of LASSO (Least Absolute Shrinkage and Selection Operator) with the Geographically Weighted Regression (GWR) model that captures the spatially varying relationship efficiently. For method details see, Wheeler, D.C.(2009).DOI:10.1068/a40256. The developed hybrid model efficiently selects the relevant variables by using LASSO as the first step; these selected variables are then incorporated into the GWR framework, allowing the estimation of spatially varying regression coefficients at unknown locations and finally predicting the values of the response variable at unknown test locations while taking into account the spatial heterogeneity of the data. Integrating the LASSO and GWR models enhances prediction accuracy by considering spatial heterogeneity and capturing the local relationships between the predictors and the response variable. The developed hybrid spatial model can be useful for spatial modeling, especially in scenarios involving complex spatial patterns and large datasets with multiple predictor variables.

Install

Health

CRAN checks
13OK
Slowest check: 1.8 min · r-devel-linux-x86_64-fedora-clang
Code health
Yes
Tests · ratio 0.08
0.0%
Coverage · measured lines
100%
Documentation · exports
5
Dependencies · direct
Check history
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  • ERROR2026-06-28
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  • ERROR2026-06-14
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  • OK2026-06-03
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  • ERROR2026-05-30
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Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
100%

Downloads

2.1K
CRAN downloads in the past year
Rank #20,014 · ~6/day · ~174/mo
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20130 days
60390 days
2.1K1 year
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Dependencies

Declared dependencies
6 external dependencies (excludes base and recommended)
Depends (1)
R >= 2.10
Imports (5)
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Code Composition
R 384 (69%)Rd 118 (21%)Vignettes 58 (10%)
Code characteristics
Cyclomatic complexity
7.0 median / 7 max
Test cases
1 / 0.08 per code line

Test coverage

Line coverage

0%

Expression

0.0%

Tests / Examples

0.0% / 100% ex

Functions

2 2 exported

Complexity

7 avg / 7 max

Call network

2 nodes / 0 edges

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Lowest coverage

2 functions
FunctionCycloCoverage
GWRLASSO_exponential exp70%
GWRLASSO_gaussian exp70%

People & History

People (7)
Maintainer (1)
Author, Maintainer, Copyright holder
Authors (7)
Author, Maintainer, Copyright holder
Author
Copyright holders (1)
Author, Maintainer, Copyright holder
Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.0Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2023-08-28
Total releases
1 / 3 yrs
License
GPL (>= 2.0)
Minimum R
≥ 2.10
Download size
11 KB
Installed size
not tracked yet
With dependencies
not tracked yet
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