redwood: California Redwoods Point Pattern (Ripley's Subset)

redwoodR Documentation

California Redwoods Point Pattern (Ripley's Subset)

Description

The data represent the locations of 62 seedlings and saplings of California Giant Redwood (Sequoiadendron giganteum) recorded in a square sampling region. They originate from Strauss (1975); the present data are a subset extracted by Ripley (1977) in a subregion that has been rescaled to a unit square. (The original physical size of the unit is approximately 63.1 feet).

Two versions of this dataset are provided: redwood and redwood3.

The dataset redwood was obtained from the spatial package. In this version the coordinates are given to 2 decimal places (multiples of 0.01 units) except for one point which has an x coordinate of 0.999, presumably to ensure that it is properly inside the window.

The dataset redwood3 was obtained from Peter Diggle's webpage. In this version the coordinates are given to 3 decimal places (multiples of 0.001 units). The ordering of the points is not the same in the two datasets.

There are many further analyses of this dataset. It is often used as a canonical example of a clustered point pattern (see e.g. Diggle, 1983).

The original, full redwood dataset is supplied in the spatstat.data package as redwoodfull.

Usage

data(redwood)

Format

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.

Source

Original data of Strauss (1975), subset extracted by Ripley (1977). Data obtained from Ripley's package spatial and from Peter Diggle's website.

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 62, 467–475.

See Also

redwoodfull


spatstat.data documentation built on May 29, 2024, 9:10 a.m.