SpatialPOP: Generation of Spatial Data with Spatially Varying Model Parameter

A spatial population can be generated based on spatially varying regression model under the assumption that observations are collected from a uniform two-dimensional grid consist of (m * m) lattice points with unit distance between any two neighbouring points. For method details see Chao, Liu., Chuanhua, Wei. and Yunan, Su. (2018).<doi:10.1080/10485252.2018.1499907>. This spatially generated data can be used to test different issues related to the statistical analysis of spatial data. This generated spatial data can be utilized in geographically weighted regression analysis for studying the spatially varying relationships among the variables.

Version:	0.1.0
Depends:	R (≥ 2.10)
Imports:	base, MASS, stats, qpdf, numbers
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2022-04-01
DOI:	10.32614/CRAN.package.SpatialPOP
Author:	Nobin Chandra Paul
Maintainer:	Nobin Chandra Paul <ncp375 at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
NeedsCompilation:	no
CRAN checks:	SpatialPOP results

Documentation:

Reference manual:	SpatialPOP.pdf
Vignettes:	SpatialPOP: package for generation of spatial data along with spatial coordinates and spatially varying model parameters

Downloads:

Package source:	SpatialPOP_0.1.0.tar.gz
Windows binaries:	r-devel: SpatialPOP_0.1.0.zip, r-release: SpatialPOP_0.1.0.zip, r-oldrel: SpatialPOP_0.1.0.zip
macOS binaries:	r-release (arm64): SpatialPOP_0.1.0.tgz, r-oldrel (arm64): SpatialPOP_0.1.0.tgz, r-release (x86_64): SpatialPOP_0.1.0.tgz, r-oldrel (x86_64): SpatialPOP_0.1.0.tgz

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