update.ppm {spatstat} | R Documentation |
update
method for class "ppm"
.
update.ppm(object, ..., Q, trend, interaction, covariates, correction, rbord, use.gam, forcefit)
object |
An existing fitted point process model,
typically produced by ppm .
|
... |
Unnamed arguments - see Details. |
Q |
a new point pattern dataset or quadrature scheme
to which the model should be fitted. An object of class
"ppp" or "quad" .
|
trend |
a new formula for the spatial trend of the model.
|
interaction |
a new interpoint interaction structure (object of class
"interact" ) for the model.
|
covariates |
a new data frame of spatial covariates,
or NULL to remove all spatial covariates.
|
correction |
character string giving a new type of edge correction,
or NULL to return to the default.
|
rbord |
numerical value of the distance for the `border' edge correction,
or NULL to suppress the border correction.
|
use.gam |
logical value indicating whether to fit the model using
gam . See ppm .
|
forcefit |
logical value controlling the use of shortcuts
when fitting trivial models. See ppm .
|
This is a method for the generic function update
for the class "ppm"
. An object of class "ppm"
describes a fitted point process model. See ppm.object
)
for details of this class.
update.ppm
will modify the point process model
specified by object
according to the new arguments given,
then re-fit it.
The actual re-fitting is performed by the model-fitting
function ppm
.
If you are comparing several model fits to the same data,
or fits of the same model to different data, it is
strongly advisable to use update.ppm
rather than trying to fit them by hand.
This is because update.ppm
re-fits the model
in a way which is comparable to the original fit.
The named arguments Q
, trend
,
interaction
, covariates
, correction
,
rbord
, use.gam
and forcefit
are passed to ppm
.
Use name=NULL
to remove the argument name
from the
call.
The unnamed arguments ...
may include
"ppp"
or "quad"
,
which will be interpreted as the named argument Q
;
"formula"
, which will be
interpreted as the named argument trend
;
"interact"
, which will be
interpreted as the named argument interaction
;
"data.frame"
, which will be
interpreted as the named argument covariates
.
Another fitted point process model (object of class "ppm"
).
Adrian Baddeley adrian@maths.uwa.edu.au http://www.maths.uwa.edu.au/~adrian/ and Rolf Turner rolf@math.unb.ca http://www.math.unb.ca/~rolf
data(nztrees) data(cells) # fit the stationary Poisson process fit <- ppm(nztrees, ~ 1) # fit a nonstationary Poisson process fitP <- update(fit, trend=~x) fitP <- update(fit, ~x) # fit a stationary Strauss process fitS <- update(fit, interaction=Strauss(13)) fitS <- update(fit, Strauss(13)) # oops, forgot the edge correction fitS <- update(fitS, rbord=13) # re-fit the model to a subset # of the original point pattern nzw <- owin(c(0,148),c(0,95)) nzsub <- nztrees[,nzw] fut <- update(fitS, Q=nzsub) fut <- update(fitS, nzsub) # WARNING: the point pattern argument is called 'Q'