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methods.lppm

Methods for Fitted Point Process Models on a Linear Network

Description

These are methods for the class "lppm" of fitted point process models on a linear network.

Usage

## S3 method for class 'lppm'
coef(object, ...)

  ## S3 method for class 'lppm'
emend(object, ...)

  ## S3 method for class 'lppm'
extractAIC(fit, ...)

  ## S3 method for class 'lppm'
formula(x, ...)

  ## S3 method for class 'lppm'
logLik(object, ...)

  ## S3 method for class 'lppm'
deviance(object, ...)

  ## S3 method for class 'lppm'
nobs(object, ...)

  ## S3 method for class 'lppm'
print(x, ...)

  ## S3 method for class 'lppm'
summary(object, ...)

  ## S3 method for class 'lppm'
terms(x, ...)

  ## S3 method for class 'lppm'
update(object, ...)

  ## S3 method for class 'lppm'
valid(object, ...)

  ## S3 method for class 'lppm'
vcov(object, ...)

  ## S3 method for class 'lppm'
as.linnet(X, ...)

Arguments

object,fit,x,X

An object of class "lppm" representing a fitted point process model on a linear network.

...

Arguments passed to other methods, usually the method for the class "ppm".

Details

These are methods for the generic commands coef, emend, extractAIC, formula, logLik, deviance, nobs, print, summary, terms, update, valid and vcov for the class "lppm".

Value

See the default methods.

Author(s)

and Ege Rubak rubak@math.aau.dk

See Also

Examples

X <- runiflpp(15, simplenet)
  fit <- lppm(X ~ x)
  print(fit)
  coef(fit)
  formula(fit)
  terms(fit)
  logLik(fit)
  deviance(fit)
  nobs(fit)
  extractAIC(fit)
  update(fit, ~1)
  valid(fit)
  vcov(fit)
spatstat.linnet

Linear Networks Functionality of the 'spatstat' Family

v2.1-1
GPL (>= 2)
Authors
Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut], Ottmar Cronie [ctb], Tilman Davies [ctb], Greg McSwiggan [ctb], Suman Rakshit [ctb]
Initial release
2021-03-28

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