# methods.rhohat

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

These are methods for the class `"rhohat"`

.

##### 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`

.

##### See Also

##### 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)
plot(simulate(rho), add=TRUE)
#
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 1.60-1, License: GPL (>= 2)*