Learn R Programming

spatstat (version 1.23-1)

redwoodfull: California Redwoods Point Pattern (Entire Dataset)

Description

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 across the region. The spatial pattern appears to be slightly regular in region I and strongly clustered in region II.

The dataset 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 ll{ 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 spatstat library as redwood. There are some minor inconsistencies with redwood since it originates from a different digitisation.

The approximate position of the square chosen by Ripley within the redwoodfull pattern is indicated by the window redwoodfull.extra$regionR.

Usage

data(redwoodfull)

Arguments

format

The dataset redwoodfull is an object of class "ppp" representing the point pattern of tree locations. The window has been rescaled to the unit square. See ppp.object for details of the format of a point pattern object.

The dataset redwoodfull.extra is a list with entries ll{ diag 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 plot Function with no arguments }

source

Strauss (1975). The plot of the data published by Strauss (1975) was scanned and digitised by Sandra Pereira, University of Western Australia, 2002.

References

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, 172--212.

Strauss, D.J. (1975) A model for clustering. Biometrika 63, 467--475.

See Also

redwood

Examples

Run this code
data(redwoodfull)
       plot(redwoodfull)
       redwoodfull.extra$plot()
       # extract the pattern in region II 
       redwoodII <- redwoodfull[, redwoodfull.extra$regionII]

Run the code above in your browser using DataLab