The spatially lagged value: for each country, the (weighted) mean of its neighbours. The building block behind every statistic here, and useful on its own – "what is happening around this country" as a regressor, a map layer or a scatter-plot axis against the country's own value (the Moran scatterplot).
Arguments
- data
A country-level frame with
iso3cand the value column.- value
The value column (unquoted).
- weights
A
country_weights()object. Defaults to land-border contiguity, which excludes islands – prefercountry_weights("knn")for global work.- suffix
Suffix for the new column (default
"_lag").
Value
data with the lagged column added. Countries the weights cannot
reach get NA – and since that NA is indistinguishable from one caused
by a missing input value, the codes themselves are attached as the
"countryatlas_excluded" attribute, the frame-shaped counterpart to the
excluded column morans_i() returns.
Examples
# \donttest{
snap <- countryatlas::world_snapshot$countries
spatial_lag(snap, gdp_per_capita, weights = country_weights("knn", k = 5))
#> # A tibble: 215 × 11
#> iso3c iso2c country continent region income gdp_per_capita population
#> <chr> <chr> <chr> <chr> <chr> <fct> <dbl> <dbl>
#> 1 AFG AF Afghanistan Asia South… Low i… NA 42647492
#> 2 ALB AL Albania Europe Europ… Upper… 6549. 2377128
#> 3 DZA DZ Algeria Africa Middl… Upper… 4766. 46814308
#> 4 ASM AS American Samoa Oceania East … High … NA 46765
#> 5 AND AD Andorra Europe Europ… High … 41035. 81938
#> 6 AGO AO Angola Africa Sub-S… Lower… 2845. 37885849
#> 7 ATG AG Antigua and Ba… Americas Latin… High … 18350. 93772
#> 8 ARG AR Argentina Americas Latin… Upper… 12774. 45696159
#> 9 ARM AM Armenia Asia Europ… Upper… 5378. 3033500
#> 10 ABW AW Aruba Americas Latin… High … 33374. 107995
#> # ℹ 205 more rows
#> # ℹ 3 more variables: life_expectancy <dbl>, co2_per_capita <dbl>,
#> # gdp_per_capita_lag <dbl>
# }