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This package extends the functionality of the kernel smoothing
functions from the ks package in base R to the
tidyverse and to GIS (Geographical Information Systems) ecosystems.
As the kernel smoothers from the ks package are prefixed
as k*, their equivalents in eks are
systematically named as follows:
tidy_k* for 1- and 2-d tidy datast_k* for 2-d geospatial data.The output data tibbles (tidy data frames provided by the
tibble package) from tidy_k* can be visualised
within the ggplot2 graphical interface, using the usual
layer functions and the custom ones supplied in this package. These
tidy_k* functions are analogous to those in the
broom and related packages, though the latter tend to focus
on tidying the summary diagnostic output from model fitting (and not on
tidying the underlying estimates themselves), whereas
tidy_k* are more substantive since they do compute tidy
estimates.
The output simple feature geometries (provided by the sf
package) from st_k* can be visualised in the (i)
ggplot2 graphical interface using primarily the
ggplot2::geom_sf layer function, or (ii) in the base
R graphical interface using the plot method
supplied in this package. These simple feature geometries can also be
exported as standard geospatial formats (e.g. shapefile, GEOS geometry)
for use in external GIS software such as ArcGIS and QGIS.
For an illustration of kernel density estimates for tidy and
geospatial data, see vignette("eks").
Install from CRAN:
install.packages("eks")Chacon, J. E. and Duong, T. (2018) Multivariate Kernel Smoothing and Its Applications Chapman & Hall/CRC Press, Boca Raton.
Duong, T. (2025) Statistical visualisation for tidy and geospatial data in R via kernel smoothing methods in the eks package Computational Statistics 40, 2825–2847.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.