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Here, p.sf is in a coordinate system different from the other layers. Note that ggplot will convert coordinate systems on-the-fly as needed. Ggplot() + geom_sf( data = s.sf, aes( fill = Income)) + geom_sf( data = rail.sf, col = "white") + geom_sf( data = p.sf, col = "green") Generate the variance and confidence interval maps.Moran’s I as a function of a distance band.Computing the Moran’s I statistic: the easy way.Computing a pseudo p-value from an MC simulation.

Computing the Moran’s I statistic: the hard way.Test for a poisson point process model with a covariate effect.Computing a pseudo p-value from the simulation.

Modeling intensity as a function of a covariate.Quadrat density on a tessellated surface.Understanding the Proj4 coordinate syntax.A note about the changes to the PROJ environment.Binary operations and functions (where two rasters are used).Unary operations and functions (applied to single rasters).Local Empirical Bayes (EB) rate estimate.Global Empirical Bayes (EB) rate estimate.Standardized mortality ratios (relative risk).Clipping spatial objects using other spatial objects.MULTIPOLYGON simple feature: multipart features.Adding a geometry column to an existing non-spatial dataframe.Step 3: Create the simple feature object sf.Step 2: Create a column of simple feature geometries: sfc.Splitting data by polygons or group of polygons.Exporting to different data file formats.Converting a raster object to an im object ( spatstat).Converting an sf point object to a ppp object.Converting an sf polygon object to an owin object.Converting an sf object to a Spatial* object ( spdep/ sp).Creating a spatial object from a data frame.A Reading and writing spatial data in R.14.2 Statistical Approach to Interpolation.14.1.3 Fine tuning the interpolation parameters.14.1 Deterministic Approach to Interpolation.13.1.2 Monte Carlo approach to estimating significance.12.4 Monte Carlo test with K and L functions.12.2.2 A better approach: a Monte Carlo test.12.2.1 ArcGIS’ Average Nearest Neighbor Tool.