The goal of wcshapes is to make spatial lagging with country-year but also other panel data easier.
Goals, basically none implemented yet:
- make a spatial lagger function that plays nicely with sf tibbles
- integrate cshapes data to make spatial lagging with country-year-like data easier
- a country-year spatial lagger solution that respects changes in state-system membership / aka unbalanced panels
- add multiple spatial weight options (see #1)
- add W normalization options (see #2)
library("remotes")
install_github("andybega/wcshapes")
NOPE NOT YET:
You can install the released version of wcshapes from CRAN with:
install.packages("wcshapes")
library("wcshapes")
library("sf")
#> Linking to GEOS 3.6.1, GDAL 2.1.3, PROJ 4.9.3
library("ggplot2")
data("est_adm1")
est_adm1$x <- as.integer(est_adm1$NAME_1 == "Harju")
w0 <- w_dist_power(st_geometry(est_adm1), alpha = .5)
w1 <- w_dist_power(st_geometry(est_adm1), alpha = 1)
w2 <- w_dist_power(st_geometry(est_adm1), alpha = 2)
est_adm1$x_sl0 <- as.numeric(w0 %*% est_adm1$x)
est_adm1$x_sl1 <- as.numeric(w1 %*% est_adm1$x)
est_adm1$x_sl2 <- as.numeric(w2 %*% est_adm1$x)
plot(est_adm1[, c("x", "x_sl0", "x_sl1", "x_sl2")])