Abstract
Abstract A popular method for reducing initialization bias in simulation output is to delay the collection of data until the model has “warmed up”. This technique, called data truncation, is considered as a special case of observation weighting. Using a simple autoregressive model for the simulated series, several optimal weighting schemes are studied.
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