# methods.rhohat

0th

Percentile

##### Methods for Intensity Functions of Spatial Covariate

These are methods for the class "rhohat".

Keywords
methods, spatial
##### Usage
# S3 method for rhohat
print(x, ...)# S3 method for rhohat
plot(x, ..., do.rug=TRUE)# S3 method for rhohat
predict(object, ..., relative=FALSE,
what=c("rho", "lo", "hi", "se"))# S3 method for rhohat
simulate(object, nsim=1, ..., drop=TRUE)
##### Arguments
x,object

An object of class "rhohat" representing a smoothed estimate of the intensity function of a point process.

Arguments passed to other methods.

do.rug

Logical value indicating whether to plot the observed values of the covariate as a rug plot along the horizontal axis.

relative

Logical value indicating whether to compute the estimated point process intensity (relative=FALSE) or the relative risk (relative=TRUE) in the case of a relative risk estimate.

nsim

Number of simulations to be generated.

drop

Logical value indicating what to do when nsim=1. If drop=TRUE (the default), a point pattern is returned. If drop=FALSE, a list of length 1 containing a point pattern is returned.

what

Optional character string (partially matched) specifying which value should be calculated: either the function estimate (what="rho", the default), the lower or upper end of the confidence interval (what="lo" or what="hi") or the standard error (what="se").

##### Details

These functions are methods for the generic commands print, plot, predict and simulate for the class "rhohat".

An object of class "rhohat" is an estimate of the intensity of a point process, as a function of a given spatial covariate. See rhohat.

The method plot.rhohat displays the estimated function $\rho$ using plot.fv, and optionally adds a rug plot of the observed values of the covariate.

The method predict.rhohat computes a pixel image of the intensity $\rho(Z(u))$ at each spatial location $u$, where $Z$ is the spatial covariate.

The method simulate.rhohat invokes predict.rhohat to determine the predicted intensity, and then simulates a Poisson point process with this intensity.

##### Value

For predict.rhohat the value is a pixel image (object of class "im" or "linim"). For simulate.rhohat the value is a point pattern (object of class "ppp" or "lpp"). For other functions, the value is NULL.

rhohat

##### Aliases
• methods.rhohat
• print.rhohat
• plot.rhohat
• predict.rhohat
• simulate.rhohat
##### Examples
# NOT RUN {
X <-  rpoispp(function(x,y){exp(3+3*x)})
rho <- rhohat(X, function(x,y){x})
rho
plot(rho)
Y <- predict(rho)
plot(Y)
#
fit <- ppm(X, ~x)
rho <- rhohat(fit, "y")
opa <- par(mfrow=c(1,2))
plot(predict(rho))
plot(predict(rho, relative=TRUE))
par(opa)
plot(predict(rho, what="se"))
# }

Documentation reproduced from package spatstat, version 1.57-1, License: GPL (>= 2)

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