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.