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, bandwidth) for a classical kernel smoothing and automatic grid. The second call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, quantiles) for a geographically weighted median and automatic grid. The third call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, centroids) for a classical kernel smoothing and user grid. The fourth call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, 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>.
Package details |
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Author | Arlindo Dos Santos [aut], François Sémécurbe [aut], Julien Pramil [aut], Kim Antunez [cre, ctb], Auriane Renaud [ctb], Farida Marouchi [ctb], Joachim Timotéo [ctb], Institut national de la statistique et des études économiques [cph] |
Maintainer | Kim Antunez <antuki.kim+cran@gmail.com> |
License | GPL (>= 2) |
Version | 0.2.0 |
URL | https://github.com/InseeFr/btb https://inseefr.github.io/btb/ |
Package repository | View on CRAN |
Installation |
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