These data represent the locations of 195 seedlings and saplings
of California redwood trees in a square sampling region.
They were described and analysed by Strauss (1975).
This is the ``full'' dataset; most writers have
analysed a subset extracted by Ripley (1977)
which is available as redwood
.
Strauss (1975) divided the sampling region into two subregions I and II demarcated by a diagonal line. The spatial pattern appears to be slightly regular in region I and strongly clustered in region II.
Strauss (1975) writes: “It was felt that the seedlings would be scattered fairly randomly, except that a number of tight clusters would form around some of the redwood tree stumps present in the plot. A discontinuity in the soil, very roughly demarked by the diagonal line in the figure, was expected to cause a difference in clustering behaviour between regions I and II. Moreover, almost all the redwood stumps were situated in region II.”
The dataset redwoodfull
contains the full point pattern
of 195 trees.
The window has been rescaled to the unit square.
Its physical size is approximately 130 feet across.
The auxiliary information about the subregions is contained in
redwoodfull.extra
, which is a list with entries
rdiag 
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) 
Ripley (1977) extracted a subset of these data, containing 62 points,
lying within a square subregion which overlaps regions I and II.
He rescaled that subset to the unit square.
This subset has been reanalysed 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 spatstat
library as redwood
.
The approximate position of the square chosen by Ripley
within the redwoodfull
pattern
is indicated by the window redwoodfull.extra$regionR
.
There are some minor inconsistencies with
redwood
since it originates from a different digitisation.
data(redwoodfull)
The dataset redwoodfull
is an object of class "ppp"
representing the point pattern of tree locations.
See ppp.object
for details of the format of a
point pattern object.
The window has been rescaled to the unit square.
Its physical size is approximately 128 feet across.
The dataset redwoodfull.extra
is a list with entries
rdiag 
coordinates of endpoints of a line, 
in format list(x=numeric(2),y=numeric(2)) 

regionI 
a window object 
regionII 
a window object 
regionR 
a window object 
Diggle, P.J. (1983) Statistical analysis of spatial point patterns. Academic Press.
Ripley, B.D. (1977) Modelling spatial patterns (with discussion). Journal of the Royal Statistical Society, Series B 39, 172212.
Strauss, D.J. (1975) A model for clustering. Biometrika 62, 467475.
# NOT RUN {
data(redwoodfull)
plot(redwoodfull)
redwoodfull.extra$plotit()
# extract the pattern in region II
redwoodII < redwoodfull[, redwoodfull.extra$regionII]
# }
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