Dear list, first let me apologise, i am an ecologist and this is my first
foray into spatial statistics.
I have, for a number of regions, the factor that best explains variation in
the yield (fisheries catch) obtained within that region, the factor has 4
levels - ChlA, SST, Effort or none.
What i am essentially wanting to know is, is there a spatial pattern to the
data? (clumped, over-dispersed or random)
For example if region 1 is classed as Effort, is it more or less likely that
the adjoining region (region 2) will be of the same factor, or does it makes
no difference.
I have seen lots of packages that allow this to be done for numerical data
but have not found one for factors.
Please see below for an example of the data. Where latitude is the centroid
of the region and factor is the source of variation.
clusters <- structure(list(Latitude = c(4.8261, 26.127123, 3.409063,
-31.964573,
11.524328, 10.857926, 30.95066, 6.322733, 40.963009, -4.370738,
53.77057, -46.270909, 51.431808, 50.091992, -12.606217, 16.26404,
-27.513126, -40.976427, -40.491914, -35.169487, -16.739053, -22.651113,
30.445027, -27.701939, -17.154608, -10.147356, -29.117245, 57.472215,
45.538569, 65.31731, 75.308501, 54.063299, 45.194528, 41.079154,
-35.169487, 51.431808, 24.647845, 68.201714, 41.262656, 24.976371,
33.251908, 16.347456, 30.95066, -1.408364, 37.054319, 23.843305,
57.400753, 8.712258), Factor = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("ChlA",
"Effort", "SST", "Unidentified"), class = "factor")), .Names = c("Latitude",
"Factor"), class = "data.frame", row.names = c(NA, -48L))
Thanks,
Chris
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