Aindex | R Documentation |
The function allows to calculate the Hodder-Okell's A index of spatial association between the
features of two point patterns.
Aindex(x, y, studyplot = NULL, B = 199, addmap = FALSE)
x |
Point pattern (SpatialPointDataframe class). |
y |
Point pattern (SpatialPointDataframe class). |
studyplot |
Feature (of polygon type; SpatialPolygonsDataFrame class) representing the study area; if not provided, the study area is internally worked out as the bounding polygon based on the union the convex hulls of the x and y patterns. This is only used for visualization purpose, should the user want to plot the two point patterns within the actual study area. |
B |
Number of permutations (199 by default). |
addmap |
FALSE (default) or TRUE if the user does not want or wants a map of the study area and of the two patterns to be displayed. |
The functions takes as input two point patterns (SpatialPointDataframe class) and calculate the A
index. Details about the latter are provided by:
Orton C. 1980, "Mathematics in Archeology",
Glasgow: William Collins Sons & Co Ltd, pp. 154-155
Blankholm P. 1990, "Intrasite spatial
Analysis in Theory and Practice", Aarhus: Aarhus University Press, pp. 130-135.
The A index is about equal to 1 when the two patterns are randomly mingled; it is smaller than 1
when the two patterns are segregated; it is larger than 1 when the features of the two point
patterns tend to occur together. The computational details are provided by Blankholm's book cited
above (page 132).
The significance of the A index is calculated via the randomized approach devised by:
Kintigh K
W. 1990, “Intrasite Spatial Analysis: A Commentary of Major Methids”. In Voorrips A, “Mathematics
and Information Science in Archaeology: A Flexible Framework”, Studies in Modern Archaeology 3:
165-200
Given two patterns A and B being analysed, the procedure keeps the points location unchanged and
randomly assigns the points to either pattern. The random re-assignment is performed B times (199
by default) and each time the A index is calculated. One-tailed and two-tailed p values are
calculated following the procedure described by Baddeley et al., "Spatial Point Patterns.
Methodology and Applications with R", CRC Press 2016, p. 387.
The function produces:
-an histogram showing the frequency distribution of the
randomized A index, with vertical reference lines representing the 0.025th and 0.975th quantile
of the distribution. A black dot represents the observed A index. At the bottom of the chart the
randomized p values are reported;
-optionally (setting the 'addmap' parameter to TRUE), a map
showing the point patterns (and the study area, if supplied).
distRandSign
, distCovarModel
,
pointsCovarModel
# calculate the Hodder-Okell's A index for the two patterns, and plot the map Aindex(springs, points, addmap=TRUE)
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