redwood. Strauss (1975) divided the sampling region into two subregions I and II demarcated by a diagonal line across the region. The spatial pattern appears to be slightly regular in region I and strongly clustered in region II.
redwoodfull contains the full point pattern
of 195 trees.
The auxiliary information about the subregions is contained in
redwoodfull.extra, which is a list with entries
diag The coordinates of the diagonal boundary
between regions I and II
regionI Region I as a window object
regionII Region II as a window object
regionR Ripley's subrectangle (approximate)
plot Function to plot the full data and auxiliary markings
Ripley (1977) extracted a subset of these data, containing 62 points,
lying within a square subregion which overlaps regions I and II.
He rescaled the data to the unit square.
This has been re-analysed many times, and is the dataset usually known as
``the redwood data'' in the spatial statistics literature.
The exact dataset used by Ripley is supplied in the
There are some minor inconsistencies with
redwood since it originates from a different digitisation.
The approximate position of the square chosen by Ripley
is indicated by the window
redwoodfullis an object of class
"ppp"representing the point pattern of tree locations. The window has been rescaled to the unit square. See
ppp.objectfor details of the format of a point pattern object.
redwoodfull.extra is a list with entries
diag coordinates of endpoints of a line,
regionI a window object
regionII a window object
regionR a window object
plot Function with no arguments
Ripley, B.D. (1977) Modelling spatial patterns (with discussion). Journal of the Royal Statistical Society, Series B 39, 172--212.
Strauss, D.J. (1975) A model for clustering. Biometrika 63, 467--475.
data(redwoodfull) plot(redwoodfull) redwoodfull.extra$plot() # extract the pattern in region II redwoodII <- redwoodfull[, redwoodfull.extra$regionII]
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