pois.lppm {GET} | R Documentation |
Fit a Poisson point process model to a point pattern dataset on a linear network
Description
Fit a Poisson point process model to a point pattern dataset on a linear network.
This function is provided in GET to support hotspots.poislpp
and
hotspots.MatClustlpp
. See the hotspots vignette available
by starting R, typing library("GET")
and vignette("GET")
.
Usage
pois.lppm(PP, formula, data, subwin = NULL, r_max = NULL)
Arguments
PP |
Input, a point pattern object (ppp) of spatstat. |
formula |
An R formula to estimate the first order model.
This formula can contain objects of full size. |
data |
Data from where the formula takes objects. Must be acceptable by the function lppm of spatstat.linnet. |
subwin |
A part of the observation window of |
r_max |
The maximum distance on which the K-function is evaluated.
Default is computed as |
Details
The function pois.lppm
, can be used to estimate the inhomogeneous
Poisson point process model on linear network. This function provides the
firstordermodel
, i.e. the regression model of dependence of crashes on
the spatial covariates, EIP
, i.e. estimated inhomogeneous intensity
from the data and secondorder
, i.e. estimation of the inhomogeneous
K-function. The plot
of the secondorder
provides diagnostics,
if the model is adequate for the data. If the estimated $K$-function lies
close to the theoretical line, the data does not report any clustering, and
the function hotspots.poislpp
can be used for final hotspots detection.
If the estimated K-function does not lie close to the theoretical line, and
it is above, the data report clustering, and the a clustered point pattern
model must be fitted to the data and hotspots detected using this clustered
model instead.