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spatstat.linnet (version 3.4-0)

linequad: Quadrature Scheme on a Linear Network

Description

Generates a quadrature scheme (an object of class "quad") on a linear network.

Usage

linequad(X, Y, ..., eps = NULL, nd = 1000, random = FALSE)

Value

A quadrature scheme (object of class "quad").

Arguments

X

Data points. An object of class "lpp" or "ppp".

Y

Line segments on which the points of X lie. An object of class "psp" or "linnet". Required only when X is a "ppp" object.

...

Ignored.

eps

Optional. Spacing between successive dummy points along each segment. (This is the maximum spacing; some spacings will be shorter.)

nd

Optional. Total number of dummy locations to be generated. (Actual number may be larger.)

random

Logical value indicating whether the sequence of dummy points should start at a randomly-chosen position along each segment.

Author

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Greg McSwiggan and Suman Rakshit.

Details

This command generates a quadrature scheme (object of class "quad") from a pattern of points on a linear network.

Normally the user does not need to call linequad explicitly. It is invoked by spatstat functions when needed. A quadrature scheme is required by lppm in order to fit point process models to point pattern data on a linear network. A quadrature scheme is also used by rhohat.lpp and other functions.

In order to create the quadrature scheme, dummy points are placed along each line segment of the network. The dummy points are evenly-spaced with spacing eps. The default is eps = totlen/nd where totlen is the total length of all line segments in the network.

Every line segment of the network will contain at least one dummy location. Consequently the actual number of dummy location generated will typically be greater than nd, especially when nd is small. If eps is specified, the number of dummy locations will be greater than totlen/eps, especially when eps is large.

If X is a multitype point pattern with \(m\) possible types, the dummy points will also be a marked point pattern. At each dummy location, \(m\) marked dummy points will be placed, one dummy point of each possible type. Additionally at each data location, a further \(m - 1\) dummy points will be placed, one dummy point of each possible type other than the type of the data point. The total number of dummy points will be \(mk + (m-1) n = m(k+n) - n\) and the total number of quadrature points will be \(m(k+n)\), where \(k\) is the number of dummy locations and \(n\) is the number of data points in X.

See Also

lppm