linearpcf | R Documentation |

Computes an estimate of the linear pair correlation function for a point pattern on a linear network.

linearpcf(X, r=NULL, ..., correction="Ang", ratio=FALSE)

`X` |
Point pattern on linear network (object of class |

`r` |
Optional. Numeric vector of values of the function argument |

`...` |
Arguments passed to |

`correction` |
Geometry correction.
Either |

`ratio` |
Logical.
If |

This command computes the linear pair correlation function from point pattern data on a linear network.

The pair correlation function is estimated from the
shortest-path distances between each pair of data points,
using the fixed-bandwidth kernel smoother
`density.default`

,
with a bias correction at each end of the interval of *r* values.
To switch off the bias correction, set `endcorrect=FALSE`

.

The bandwidth for smoothing the pairwise distances
is determined by arguments `...`

passed to `density.default`

, mainly the arguments
`bw`

and `adjust`

. The default is
to choose the bandwidth by Silverman's rule of thumb
`bw="nrd0"`

explained in `density.default`

.

If `correction="none"`

, the calculations do not include
any correction for the geometry of the linear network. The result is
an estimate of the first derivative of the
network *K* function defined by Okabe and Yamada (2001).

If `correction="Ang"`

, the pair counts are weighted using
Ang's correction (Ang, 2010). The result is an estimate of the
pair correlation function in the linear network.

Function value table (object of class `"fv"`

).

If `ratio=TRUE`

then the return value also has two
attributes called `"numerator"`

and `"denominator"`

which are `"fv"`

objects
containing the numerators and denominators of each
estimate of *g(r)*.

Ang Qi Wei aqw07398@hotmail.com and \adrian.

Ang, Q.W. (2010) Statistical methodology for spatial point patterns on a linear network. MSc thesis, University of Western Australia.

Ang, Q.W., Baddeley, A. and Nair, G. (2012)
Geometrically corrected second-order analysis of
events on a linear network, with applications to
ecology and criminology.
*Scandinavian Journal of Statistics* **39**, 591–617.

Okabe, A. and Yamada, I. (2001) The K-function method on a network and
its computational implementation. *Geographical Analysis*
**33**, 271-290.

`linearK`

,
`linearpcfinhom`

,
`lpp`

data(simplenet) X <- rpoislpp(5, simplenet) linearpcf(X) linearpcf(X, correction="none")

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