lohboot(X,
          fun=c("pcf", "Kest", "pcfinhom", "Kinhom"),
          ..., nsim=200, confidence=0.95, global=FALSE, type=7)"ppp")."pcf", "Kest", "pcfinhom" or "Kinhom".FALSE (the default), pointwise confidence intervals
    are constructed. If TRUE, a global (simultaneous) confidence band is
    constructed.quantile
    controlling the way the quantiles are calculated."fv")
  containing columns giving the estimate of the summary function,
  the upper and lower limits of the bootstrap confidence interval,
  and the theoretical value of the summary function for a Poisson process.fun using the bootstrap method of Loh (2008).  If fun="pcf", for example, the algorithm computes a pointwise
  (100 * confidence)% confidence interval for the true value of
  the pair correlation function pcf for the point
  process. It starts by computing the array of
  local pair correlation functions,
  localpcf, of the data pattern X.
  This array consists of the contributions to pcf from each
  data point. Then these contributions are resampled nsim times
  with replacement; from each resampled dataset the total contribution
  is computed, yielding nsim random pair correlation functions.
  The pointwise alpha/2 and 1 - alpha/2 quantiles of
  these functions are computed, where alpha = 1 - confidence.
  To control the smoothing and estimation algorithm, use the 
  arguments ..., which are passed to the local version
  of the summary function, as shown below:
  
  pcf 	localpcf 
Kest 	localK 
pcfinhom 	localpcfinhom 
Kinhom 	localKinhom
  }
  An alternative to lohboot is varblock.
Kest,
  pcf,
  Kinhom,
  pcfinhom,
  localK,
  localpcf,
  localKinhom,
  localpcfinhom.  See varblock for an alternative bootstrap technique.
p <- lohboot(simdat, stoyan=0.5)
  plot(p)Run the code above in your browser using DataLab