Abstract:
Many powerful statistical methods available for studying simulation output are under-appreciated and consequently under-used, because they are considered to be hard-to-un...Show MoreMetadata
Abstract:
Many powerful statistical methods available for studying simulation output are under-appreciated and consequently under-used, because they are considered to be hard-to-understand, arcanely mathematical, and hard to implement. Such methods can invariably be implemented using data-driven resampling methods, making their underlying rationale quite transparent. There is little need for much formal mathematics, and what there is can be made visually obvious, with method and results explained and presented using figures and graphs, often with dynamic animation. This approach in studying simulation output will be illustrated by a number of examples drawn from simulation studies and real applications. A bonus of the approach is that it is quite easy to create one’s own ‘bespoke’ method of analysis tailored to a particular problem. Such examples will be presented and analyzed in ‘real-time’ in the talk itself, enabling the results to be immediately displayed.
Published in: 2018 Winter Simulation Conference (WSC)
Date of Conference: 09-12 December 2018
Date Added to IEEE Xplore: 03 February 2019
ISBN Information: