Complementary antithetic weights for lognormal time-series forecasting
A simplified antithetic time-series model is presented. Two independent combining weights are replaced by a single weight and its complement. The number of computations and the time required to perform them are thereby reduced. The fitting of a time-series model to serially correlated data often results in model parameters that are biased. The fitted values obtained from such a model are in turn biased. This is quite often unavoidable. Antithetic time-series modeling is a process for removing bias from the fitted values. The process may be retrofitted to any time-series model.
time series forecasting antithetic combining stochastic processes power transformation optimization