btb: Beyond the Border - Kernel Density Estimation for Urban Geography

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

Getting started

Package details

AuthorArlindo Dos Santos [cre], Francois Semecurbe [drt, aut], Auriane Renaud [ctb], Cynthia Faivre [ctb], Thierry Cornely [ctb], Farida Marouchi [ctb], Farida Marouchi [ctb]
MaintainerArlindo Dos Santos <[email protected]>
LicenseGPL (>= 2)
Version0.1.30
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("btb")

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btb documentation built on May 23, 2018, 5:04 p.m.