rpoislpp {spatstat.linnet}

Poisson Point Process on a Linear Network

Description

Generates a realisation of the Poisson point process with specified intensity on the given linear network.

Usage

rpoislpp(lambda, L, ..., nsim=1, drop=TRUE, ex=NULL)

Arguments

lambda

Intensity of the Poisson process. A single number, a function(x,y), a pixel image (object of class "im"), or a vector of numbers, a list of functions, or a list of images.

L

A linear network (object of class "linnet", see linnet). Can be omitted in some cases: see Details.

...

Arguments passed to rpoisppOnLines.

nsim

Number of simulated realisations to generate.

drop

Logical value indicating what to do when nsim=1. If drop=TRUE (the default), the result is a point pattern. If drop=FALSE, the result is a list with one entry which is a point pattern.

ex

Optional. A point pattern on a network (object of class "lpp") which serves as an example to determine the default values of lambda and L. See Details.

Details

A random number of random points is generated on the network L, according to a Poisson point process with intensity lambda points per unit length. The random points are generated by rpoisppOnLines. See the help file for rpoisppOnLines for information.

Argument L can be omitted, and defaults to as.linnet(lambda), when lambda is a function on a linear network (class "linfun") or a pixel image on a linear network ("linim").

If ex is given, then it serves as an example for determining lambda and L. The default value of lambda will be the average intensity (number per unit length) of points in ex (or the average intensity of the points of each type if ex is multitype). The default value of L will be the network on which ex is defined.

Value

If nsim = 1 and drop=TRUE, a point pattern on the linear network, i.e.\ an object of class "lpp". Otherwise, a list of such point patterns.

Author(s)

Ang Qi Wei [e-mail] and Adrian Baddeley [e-mail]

See Also

rpoisppOnLines, runiflpp, rlpp, lpp, linnet.

Examples

   X <- rpoislpp(5, simplenet)
   plot(X)
   # multitype
   Y <- rpoislpp(c(a=5, b=5), simplenet)
   # using argument 'ex' to make a pattern like 'X'
   Z <- rpoislpp(ex=X)