japanesepines

The data give the locations of Japanese black pine saplings
 in a square sampling region in a natural forest.
 The observations were originally collected by Numata (1961). These data are used as a standard example in the textbook of 
 Diggle (2003); see pages 1, 14, 19, 22, 24, 56--57 and 61.

datasets

spatial

A package for analysing spatial data,
	mainly Spatial Point Patterns,
	including multitype/marked points and spatial covariates,
	in any two-dimensional spatial region.
	Contains functions for exploratory data analysis,
	model-fitting, simulation, spatial sampling, model diagnostics,
	and formal inference. Data types include point patterns,
	line segment patterns, spatial windows, and
	pixel images. Point process models can be
	fitted to point pattern data. Cluster type models are fitted
	by the method of minimum contrast. Very general Gibbs point
	process models can be fitted to point pattern data
	using a function ppm similar to lm or glm. Models may
	include dependence on covariates, interpoint interaction
	and dependence on marks. Fitted models can be simulated automatically.
	Also provides facilities for formal inference (such as chi-squared
	tests) and model diagnostics (including simulation
	envelopes, residuals, residual plots and Q-Q plots).

Adrian Baddeley

spatstat

Spatial Point Pattern analysis, model-fitting, simulation, tests

japanesepines function

An object of class <code>"ppp"</code>
 representing the point pattern of tree locations
 in a 5.7 x 5.7 metre square, rescaled to the unit square
 and rounded to two decimal places. See <code><a href="/link/ppp.object?package=spatstat&version=1.11-4" rd-options="" data-mini-rdoc="spatstat::ppp.object">ppp.object</a></code> for details of the format of a
 point pattern object.

format

Diggle (2003), obtained from Numata (1961)

japanesepines: Japanese Pines Point Pattern

Description

Usage

Arguments

format

source

References