LennardJones(sigma0=NA)"interact"
  describing the Lennard-Jones interpoint interaction
  structure.
d are rescaled
  when fitting the model. Distances are rescaled by dividing by sigma0.
  In the formula for $v(d)$ above,
  the interpoint distance $d$ will be replaced by d/sigma0. The rescaling happens automatically by default.
  If the argument sigma0 is missing or NA (the default),
  then sigma0 is taken to be the minimum
  nearest-neighbour distance in the data point pattern (in the
  call to ppm). If the argument sigma0 is given, it should be a positive
  number, and it should be a rough estimate of the
  parameter $sigma$. The ``canonical regular parameters'' estimated by ppm are
  $theta1 = 4 * epsilon * (sigma/sigma0)^12$
  and 
  $theta2 = 4 * epsilon * (sigma/sigma0)^6$.gcontrol=list(maxit=1e3) in the call to ppm. Errors are likely to occur if this model is fitted to a point pattern dataset
  which does not exhibit both short-range inhibition and
  medium-range attraction between points.  The values of the parameters
  $sigma$ and $epsilon$ may be NA
  (because the fitted canonical parameters have opposite sign, which
  usually occurs when the pattern is completely random). An absence of warnings does not mean that the fitted model is sensible.
  A negative value of $epsilon$ may be obtained (usually when
  the pattern is strongly clustered); this does not correspond
  to a valid point process model, but the software does not issue a warning.  This potential is used 
  to model interactions between uncharged molecules in statistical physics.
  
  The function ppm(), which fits point process models to 
  point pattern data, requires an argument 
  of class "interact" describing the interpoint interaction
  structure of the model to be fitted. 
  The appropriate description of the Lennard-Jones pairwise interaction is
  yielded by the function LennardJones().
  See the examples below.
ppm,
  pairwise.family,
  ppm.object
   fit <- ppm(cells ~1, LennardJones(), rbord=0.1)
   fit
   plot(fitin(fit))
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