Dear R-sig-geo,
I am fairly new to R and very new to spatial regression models. I am
attempting to compare an OLS model to some sort of spatial regression
such as SAR. However, I am unclear about how to properly designate the
spatial neighbors and weights and hope that someone can provide
guidance.
My data set consists of variables taken from a series of irregularly
shaped and spaced polygons, some are spatial nested (one completely
inside another). I have approximate centroids for the polygons as well
as some values for the max and min latitude and longitude of each. I am
using the centroids in the example below. I have been using Bivand et
al. (Applied Spatial Data Analysis with R) as a guide but my data is a
bit different then the examples provided.
I am attempting to make a weight file based on the distance based
neighbors. I have pasted some example code below. My thought was that
using distance based neighbors would associate the nested as well as
some of the areas that are close by. This method seems to leave me with
some areas without neighbors. This seems to cause a problem when I
attempt to convert the 'nb' to the 'listw'.
Can anyone provide me with guidance as to how to proceed or how to best
associated the areas in my data set. Thank you in advance for any help!
library(spdep)
my.lat <- c(36.4000, 36.3908, 35.0550, 36.0226, 36.4472, 36.1450, 35.2680,
35.1335,
35.3225, 35.0050, 35.0450, 35.0600, 35.0500, 35.6120, 35.4330, 36.4580,
35.8850, 35.7647, 35.8842, 35.6135, 36.3915, 35.1290, 35.4769, 34.9881,
35.4267, 35.5986, 35.8927, 35.4721, 35.4684, 35.6802, 35.6413, 36.2405,
35.3650, 35.8183, 36.5495, 35.7250, 36.1955, 35.5960, 35.6300, 35.8930,
35.2360, 35.1400, 35.1970, 36.5000, 35.1540, 35.5432, 35.8898, 35.5389,
35.8641, 35.6340, 35.4560, 35.3630, 35.4270, 35.7080, 35.7930, 36.1020,
35.0127, 35.1380, 35.1310, 35.5689, 35.5417, 35.5206, 35.5634, 35.5157,
35.9020, 35.8975, 35.8843, 35.8872)
my.long <- c(-81.4614, -81.5717, -83.4550, -81.8264, -81.0608, -81.8070,
-82.4525,
-79.8415, -82.5035, -83.1400, -83.0000, -82.9500, -82.9500, -83.7800,
-82.2475,
-81.4715, -81.8815, -82.2653, -78.5282, -79.1614, -81.0700, -79.1500,
-76.8119,
-79.5515, -80.0516, -81.6531, -78.5834, -76.9099, -78.9180, -80.9803,
-80.5191,
-77.8615, -80.0825, -78.8575, -76.3840, -78.7000, -78.8034, -79.1300,
-83.5200,
-79.0300, -77.8800, -79.2200, -77.8700, -76.1245, -79.1400, -79.3216,
-79.0232,
-79.2881, -78.7555, -83.4000, -83.1300, -82.9200, -82.7600, -82.3700,
-82.2900,
-82.1100, -82.8264, -81.3900, -81.3700, -83.6629, -83.4933, -83.8661,
-83.7328,
-83.8830, -79.0390, -79.0305, -79.0469, -79.0166)
my.coords <- as.matrix(cbind(my.long,my.lat))
nb40km <- dnearneigh(my.coords,0,40, longlat = TRUE)
plot(my.coords)
plot(nb40km, my.coords, add = TRUE)
