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remap (version 0.3.2)

Regional Spatial Modeling with Continuous Borders

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) .

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Install

install.packages('remap')

Monthly Downloads

278

Version

0.3.2

License

GPL-3

Issues

0

Pull Requests

0

Stars

1

Forks

0

Maintainer

Jadon Wagstaff

Last Published

January 9th, 2025

Functions in remap (0.3.2)

get_geo_position

Get the location information of the city vector
get_theme

Create a theme object for remap
markLineControl

Control the theme of mark line
markPointControl

Control the theme of mark Point
REmapOutput

Plot REmap in shiny
get_city_coord

Get the location information of the city
remap.init

Remap initial for knitr
remapB

Create a Bmap object
plot.remap

Plot method for remap object.
remap

Build separate models for mapping multiple regions.
remapC

Create a choropleth map object
remapH

Create a heat map
knitrREmap

Plot REmap in knitr
mapNames

Get the names of a choropleth map for remapC
redist

Get distances between data and regions.
predict.remap

Make predictions given a set of data and smooths predictions at region borders. If an observation is outside of all regions and smoothing distances, the closest region will be used to predict.
utws

Watershed polygons within the state of Utah.
summary.remap

Summary method for remap object.
print.remap

Print method for remap object.
utsnow

Snowpack at weather stations in Utah on April 1st, 2011.