Computational Options for Loess Fitting
DESCRIPTION:
Allows the user to specify computational options used within the control argument of loess.
USAGE: 
loess.control(surface=c("interpolate", "direct"), statistics=
      c("approximate", "exact"), trace.hat=c("wait.to.decide",
      "approximate", "exact"), cell=0.2, iterations=4,
      method=c("loess", "model.frame"), ...)
OPTIONAL ARGUMENTS:
surface:
determines whether the fitted surface is computed directly at all points ("direct") or whether an interpolation method is used ("interpolate"). The latter, the default, is what most users should use unless special circumstances warrant.
statistics:
determines whether the statistical quantities are computed exactly ("exact") or approximately ("approximate"). The latter is the default. The former should only be used for testing the approximation in statistical development and is not meant for routine usage because computation time can be horrendous.
trace.hat:
when surface is "approximate", determines the computational method used to compute the trace of the hat matrix, which is used in the computation of the statistical quantities. If "exact", an exact computation is done; normally this goes quite fast on the fastest machines until n, the number of observations is 1000 or more, but for very slow machines, things can slow down at n = 300. If "wait.to.decide" is selected, then a default is chosen in loess; the default is "exact" for n < 500 and "approximate" otherwise. If surface is "exact", an exact computation is always done for the trace.
cell:
if interpolation is used to compute the surface, this argument specifies the maximum cell size of the k-d tree. Suppose k <- floor(n*cell*span) where n is the number of observations. Then a cell is further divided if the number of observations within it is greater than or equal to k.
iterations:
if family is "symmetric", the number of iterations of the robust fitting method.
method:
determines the returned object. If "loess", the default, the loess object is returned. If "model.frame", the model frame is returned.
VALUE:
a list with the following components:
surface:
value of the argument surface.
statistics:
value of the argument statistics.
trace.hat:
value of the argument trace.hat.
cell:
value of the argument cell.
iterations:
value of the argument iterations.
method:
value of the argument method.
DETAILS:
This function can be used to create a list that is given as the value of the argument control of the function loess. Most users need not specify control since its defaults provide satisfactory performance in most cases. Changing the surface evaluation method to exact can increase the computational burden slightly for small data sets and by a substantial amount for large data sets. Changing the method of computing statistics to exact can cause a catastrophic computation time except perhaps in supercomputer environments. The arguments of loess.control can be specified directly in a call to loess for a temporary change in the computational methods. The user, however, can achieve a lasting change by rewriting loess.control with new defaults.
SEE ALSO:
loess , predict.loess , plot.loess , pointwise , anova.loess , specs.loess , preplot.loess .
EXAMPLES: 
loess(NOx ~ C * E, data = ethanol, span = 1/2, drop.square = "C",
      parametric = "C", control = loess.control(surface = "direct"))
# The following has the same result:
loess(NOx ~ C * E, data = ethanol, span = 1/2, drop.square = "C",
      parametric = "C", surface = "direct")