Transcription of Analysing Spatial Data in R: Worked example: …
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Analysing Spatial Data in R: Worked example: …
Analysing Spatial Data in R: Worked example: geostatisticsRoger BivandDepartment of EconomicsNorwegian School of Economics and Business AdministrationBergen, Norway31 August 2007 Worked example: geostatisticsIGeostatistics is a bit like the alchemy of Spatial statistics,focussed more on prediction than model fittingISince the reason for modelling is chiefly prediction inpre-model-based geostatistics , and to a good extent inmodel-based geostatistics , we ll also keep to interpolation hereIInterpolation is trying to make as good guesses as possible ofthe values of the variable of interest for places where there areno observations (can be in 1, 2, 3,..dimensions)IThese are based on the relative positions of places withobservations and places for which predictions are required, andthe observed values at observationsGeostatistics packagesIThegstatpackage provides a wide range of functions forunivariate and multivariate geostatistics , also for largerdatasets, whilegeoRandgeoRglmcontain functions formodel-based geostatisticsIA similar wide range of functions is to be found in thefieldspackage.
Worked example: geostatistics I Geostatistics is a bit like the alchemy of spatial statistics, focussed more on prediction than model fitting I Since the reason for modelling is chiefly prediction in
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