Summarizing a Fitted Point Process Model
summary method for class "ppm".
## S3 method for class 'ppm' summary(object, ..., quick=FALSE, fine=FALSE) ## S3 method for class 'summary.ppm' print(x, ...)
object |
A fitted point process model. |
... |
Ignored. |
quick |
Logical flag controlling the scope of the summary. |
fine |
Logical value passed to |
x |
Object of class |
This is a method for the generic summary
for the class "ppm". An object of class "ppm"
describes a fitted point process model. See ppm.object)
for details of this class.
summary.ppm extracts information about the
type of model that has been fitted, the data to which the model was
fitted, and the values of the fitted coefficients.
(If quick=TRUE then only the information about the type
of model is extracted.)
print.summary.ppm prints this information in a
comprehensible format.
In normal usage, print.summary.ppm is invoked implicitly
when the user calls summary.ppm without assigning its value
to anything. See the examples.
You can also type coef(summary(object)) to extract a table
of the fitted coefficients of the point process model object
together with standard errors and confidence limits.
summary.ppm returns an object of class "summary.ppm",
while print.summary.ppm returns NULL.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
and Rolf Turner r.turner@auckland.ac.nz
# invent some data
X <- rpoispp(42)
# fit a model to it
fit <- ppm(X ~ x, Strauss(r=0.1))
# summarize the fitted model
summary(fit)
# `quick' option
summary(fit, quick=TRUE)
# coefficients with standard errors and CI
coef(summary(fit))
coef(summary(fit, fine=TRUE))
# save the full summary
s <- summary(fit)
# print it
print(s)
s
# extract stuff
names(s)
coef(s)
s$args$correction
s$name
s$trend$value
# multitype pattern
# data(demopat)
# fit <- ppm(demopat, ~marks, Poisson())
# summary(fit)
# model with external covariates
fitX <- ppm(X, ~Z, covariates=list(Z=function(x,y){x+y}))
summary(fitX)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.