Approximation des dissimilarités par des arbres additifs
AR models with uniformly distributed noise
AR models are frequently used but usually with normally distributed white noise. In this paper AR model with uniformly distributed white noise are introduces. The maximum likelihood estimation of unknown parameters is treated, iterative method for the calculation of estimates is presented. A numerical example of this procedure and simulation results are also given.
Automatic run-time choice for simulation length in mimesis
Automatic run-time choice for simulation length in mimesis
This paper presents an algorithm which prevents a simulation user from choosing a simulation length. This choice is always tricky and often leads to CPU-time waste, not to mention user-time waste. Too often, simulation users forget to compute confidence intervals: they only guess a simulation length and ignore the confidence on the simulation results. Those who do compute them generally try several lengths (and thus run several simulations) so as to obtain small enough confidence intervals. The...