| Type: | Package |
| Title: | Generation of Spatial Data with Spatially Varying Model Parameter |
| Version: | 0.1.0 |
| Author: | Nobin Chandra Paul |
| Maintainer: | Nobin Chandra Paul<ncp375@gmail.com> |
| Depends: | R(≥ 2.10) |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| VignetteBuilder: | knitr |
| Description: | 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. |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)] |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.1.2 |
| Imports: | base,MASS,stats, qpdf, numbers |
| NeedsCompilation: | no |
| Packaged: | 2022-03-31 17:28:08 UTC; nobin ch paul |
| Repository: | CRAN |
| Date/Publication: | 2022-04-01 07:50:02 UTC |
Generation of Spatial Data with Spatial Coordinates and Spatially Varying Model Parameters
Description
Generation of Spatial Data with Spatial Coordinates and Spatially Varying Model Parameters
Usage
spatialPOP(N, m, xlat, ylong)
Arguments
N |
integer; population size i.e. N= (m * m) |
m |
integer |
xlat |
numeric vector |
ylong |
numeric vector |
Value
returns a dataframe of spatially generated population consist of simulated response variable (i.e. Y) along with their spatial coordinates, spatially varying model parameters and one explanatory variable (i.e. X)
References
1. Leung, Y., Mei, C. L. and Zhang, W. X. (2000). Statistical tests for spatial non-stationarity based on the geographically weighted regression model. Environment and Planning A, 32(1), 9-32.
2. Chao, Liu., Chuanhua, Wei. and Yunan, Su. (2018). Geographically weighted regression model-assisted estimation in survey sampling. Journal of Nonparametric Statistics. <DOI:10.1080/10485252.2018.1499907>.
Examples
lattice_points<-spatial_grid(c(1:10),c(1:10))
spatial_data<-spatialPOP(100,10,c(1:10),c(1:10))
a uniform two dimensional grid of lattice points
Description
a uniform two dimensional grid of lattice points
Usage
spatial_grid(lat, long)
Arguments
lat |
numeric vector |
long |
numeric vector |
Value
returns a dataframe of lattice points
Examples
spatial_grid(c(1:10),c(1:10))