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 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 spatstat
library as redwood
.
The approximate position of the square chosen by Ripley
within the redwoodfull
pattern
is indicated by the window redwoodfull.extra$regionR
.
There are some minor inconsistencies with
redwood
since it originates from a different digitisation.
data(redwoodfull)
redwoodfull
is an object of class "ppp"
representing the point pattern of tree locations.
See ppp.object
for details of the format of a
point pattern object.
The window has been rescaled to the unit square.
Its physical size is approximately 128 feet across. The dataset redwoodfull.extra
is a list with entries
rdiag |
coordinates of endpoints of a line, |
in format list(x=numeric(2),y=numeric(2)) |
regionI |
a window object |
regionII |
a window object |
regionR |
a window object |
Ripley, B.D. (1977) Modelling spatial patterns (with discussion). Journal of the Royal Statistical Society, Series B 39, 172--212.
Strauss, D.J. (1975) A model for clustering. Biometrika 62, 467--475.
redwood
data(redwoodfull)
plot(redwoodfull)
redwoodfull.extra$plotit()
# extract the pattern in region II
redwoodII <- redwoodfull[, redwoodfull.extra$regionII]
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