model
one of "wn" (white noise), "ou" or "ouf" (case insensitive), denoting, respectively, no autocorrelation, position autocorrelation, or velocity and position autocorrelation. If model = NULL and method = "ar", the algorithm will select a model using AIC comparisons of the three. If the selected model iswhite noise, the function will return 0's for both parameters.
method
either "like" or "ar". The former refers to the likelihood method - it is most general (i.e. works with irregular sampling). The latter refers to the auto-rgressive model equivalence, which is faster but only works with regular sampling.