/btb

An R package which provides functions dedicated to urban analysis and kernel density estimation.

Primary LanguageC++GNU General Public License v3.0GPL-3.0

Beyond the Border

R-CMD-check

CRAN_Status

btb ("Beyond the Border - Kernel Density Estimation for Urban Geography") is an R package which provides functions dedicated to urban analysis and density estimation using the KDE (kernel density estimator) method.

A partial transposition of the package in Python is also available: btbpy.

Description

The btb_smooth() function allows you to square and smooth geolocated data. It calculates a classical kernel smoothing (conservative) or a geographically weighted median. There are four major call modes of the function.

  • The first call mode is btb_smooth(obs, epsg, cellsize, bandwith) for a classical kernel smoothing and automatic grid.
  • The second call mode is btb_smooth(obs, epsg, cellsize, bandwith, quantiles) for a geographically weighted median and automatic grid.
  • The third call mode is btb_smooth(obs, epsg, cellsize, bandwith, centroids) for a classical kernel smoothing and user grid.
  • The fourth call mode is btb_smooth(obs, epsg, cellsize, bandwith, quantiles, centroids) for a geographically weighted median and user grid.

Installation

btb is available on CRAN and can therefore be readily installed

install.packages("btb")

To get a bug fix or to use a feature from the development version, you can install the development version of from GitHub :

install.packages("devtools")
devtools::install_github("InseeFr/btb")

Usage

Details on how to use the package can be found in its documentation. Some applications for spatial smoothing are presented in chapter 8 of the Handbook of Spatial Analysis published by Insee. You advise you to start by consulting the vignette of the package

Contributions

Maintainer: Kim Antunez antuki.kim+cran@gmail.com

Creators, authors and contributors:

  • Arlindo DOS SANTOS [cre],
  • François SEMECURBE [cre],
  • Julien PRAMIL [aut]
  • Kim ANTUNEZ [ctb],
  • Auriane RENAUD [ctb],
  • Farida MAROUCHI [ctb]
  • Joachim TIMOTEO [ctb]

References

  • Geographically weighted summary statistics : a framework for localised exploratory data analysis, C.Brunsdon & al., in Computers, Environment and Urban Systems C.Brunsdon & al. (2002) doi:10.1016/S0198-9715(01)00009-6
  • Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition, Diggle, pp. 83-86, (2003) doi:10.1080/13658816.2014.937718.