Description Usage Format Note Source Examples

The `afcon`

data frame has 42 rows and 5 columns, for 42 African
countries, exclusing then South West Africa and Spanish Equatorial Africa
and Spanish Sahara. The dataset is used in Anselin (1995), and downloaded
from before adaptation. The neighbour list object `africa.rook.nb`

is the SpaceStat ‘rook.GAL’, but is not the list used in Anselin
(1995) - `paper.nb`

reconstructs the list used in the paper, with
inserted links between Mauritania and Morocco, South Africa and Angola
and Zambia, Tanzania and Zaire, and Botswana and Zambia. `afxy`

is the coordinate matrix for the centroids of the countries.

1 |

This data frame contains the following columns:

- x
an easting in decimal degrees (taken as centroid of shapefile polygon)

- y
an northing in decimal degrees (taken as centroid of shapefile polygon)

- totcon
index of total conflict 1966-78

- name
country name

- id
country id number as in paper

All source data files prepared by Luc Anselin, Spatial Analysis Laboratory, Department of Agricultural and Consumer Economics, University of Illinois, Urbana-Champaign.

Anselin, L. and John O'Loughlin. 1992. Geography of international conflict and cooperation: spatial dependence and regional context in Africa. In The New Geopolitics, ed. M. Ward, pp. 39-75. Philadelphia, PA: Gordon and Breach. also: Anselin, L. 1995. Local indicators of spatial association, Geographical Analysis, 27, Table 1, p. 103.

1 2 3 4 5 6 7 | ```
data(afcon)
plot(africa.rook.nb, afxy)
plot(diffnb(paper.nb, africa.rook.nb), afxy, col="red", add=TRUE)
text(afxy, labels=attr(africa.rook.nb, "region.id"), pos=4, offset=0.4)
moran.test(afcon$totcon, nb2listw(africa.rook.nb))
moran.test(afcon$totcon, nb2listw(paper.nb))
geary.test(afcon$totcon, nb2listw(paper.nb))
``` |

```
Loading required package: sp
Loading required package: Matrix
Moran I test under randomisation
data: afcon$totcon
weights: nb2listw(africa.rook.nb)
Moran I statistic standard deviate = 4.1251, p-value = 1.853e-05
alternative hypothesis: greater
sample estimates:
Moran I statistic Expectation Variance
0.40981723 -0.02439024 0.01107950
Moran I test under randomisation
data: afcon$totcon
weights: nb2listw(paper.nb)
Moran I statistic standard deviate = 4.3485, p-value = 6.854e-06
alternative hypothesis: greater
sample estimates:
Moran I statistic Expectation Variance
0.41679563 -0.02439024 0.01029358
Geary C test under randomisation
data: afcon$totcon
weights: nb2listw(paper.nb)
Geary C statistic standard deviate = 2.8988, p-value = 0.001873
alternative hypothesis: Expectation greater than statistic
sample estimates:
Geary C statistic Expectation Variance
0.58395772 1.00000000 0.02059931
```

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