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README

Beyond the Border

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, bandwidth) for a classical kernel smoothing and automatic grid.
The second call mode is btb_smooth(obs, epsg, cellsize, bandwidth, quantiles) for a geographically weighted median and automatic grid.
The third call mode is btb_smooth(obs, epsg, cellsize, bandwidth, centroids) for a classical kernel smoothing and user grid.
The fourth call mode is btb_smooth(obs, epsg, cellsize, bandwidth, 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 [aut],
François SEMECURBE [aut],
Julien PRAMIL [aut]
Kim ANTUNEZ [cre, 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.