From Luc:
no need to add afcon. it’s a very small data set and misses some countries, so it looks weird.
it was used as the example in the LISA paper, but the sample size is too small for “modern” use.
a few of them are “classic” (but then also old), such as
Auckland (used in an early paper to illustrate EB smoothing)
Elect80 (US counties election results), used as example for spatial probit, but
from the looks of it, it doesn’t have the 0-1. we have a better one from LeSage
with the 1996 elections (I used in my Brown class — I can produce if we don’t
have it)
house: Lucas county housing data (points) - is originally from LeSage toolbox
NY_Data is Leukemia data from the Waller-Gotway book, as points
(it would be nice to supplement with the actual tract areas as polygons)
but typically these data sets have very few variables, so not that useful.
low priority - for later: R sample data
http://origin.rdrr.io/rforge/splm/ splm/data/Insurance.rda splm/data/RiceFarms.rda splm/data/itaww.rda splm/data/riceww.rda splm/data/usaww.rda
http://origin.rdrr.io/rforge/spdep/ spdep/data/NY_data.rda spdep/data/afcon.rda spdep/data/auckland.rda spdep/data/baltimore.rda spdep/data/boston.rda spdep/data/columbus.rda spdep/data/datalist spdep/data/eire.rda spdep/data/elect80.rda spdep/data/getisord.rda spdep/data/hopkins.rda spdep/data/house.RData spdep/data/huddersfield.rda spdep/data/nc.sids.rda spdep/data/oldcol.rda spdep/data/used.cars.rda spdep/data/wheat.rda
From Luc: no need to add afcon. it’s a very small data set and misses some countries, so it looks weird. it was used as the example in the LISA paper, but the sample size is too small for “modern” use.
a few of them are “classic” (but then also old), such as