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remap  

Regional Spatial Modeling with Continuous Borders
View on CRAN: Click here


Download and install remap package within the R console
Install from CRAN:
install.packages("remap")

Install from Github:
library("remotes")
install_github("cran/remap")

Install by package version:
library("remotes")
install_version("remap", "0.3.1")



Attach the package and use:
library("remap")
Maintained by
Jadon Wagstaff
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-01-14
Latest Update: 2023-06-14
Description:
Automatically creates separate regression models for different spatial regions. The prediction surface is smoothed using a regional border smoothing method. If regional models are continuous, the resulting prediction surface is continuous across the spatial dimensions, even at region borders. Methodology is described in Wagstaff and Bean (2023) .
How to cite:
Jadon Wagstaff (2021). remap: Regional Spatial Modeling with Continuous Borders. R package version 0.3.1, https://cran.r-project.org/web/packages/remap. Accessed 21 Dec. 2024.
Previous versions and publish date:
0.2.0 (2021-01-14 11:30), 0.2.1 (2021-04-16 17:50), 0.3.0 (2022-08-13 01:10)
Other packages that cited remap R package
View remap citation profile
Other R packages that remap depends, imports, suggests or enhances
Complete documentation for remap
Functions, R codes and Examples using the remap R package
Some associated functions: plot.remap . predict.remap . print.remap . redist . remap . summary.remap . utsnow . utws . 
Some associated R codes: data.R . redist.R . remap.R . utils.R .  Full remap package functions and examples
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