Mathematical Sciences: Statistical Analysis for Stochastic  Modeling and Simulation with Applications to Manufacturing  Systems
{'Code': '03040300', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
{'SignBlockName': 'Joseph M. Rosenblatt', 'PO_EMAI': None, 'PO_PHON': None}
Statistical problems in simulation to be studied include                   modeling input processes, analyzing output, reducing variance,                  and designing simulation experiments.  Statistical and                          computational problems involving simulation are motivated by the                need to calculate complicated statistical quantities.  Most of                  the problems center around integration, both high dimensional                   integration and simultaneous integration of thousands of related                integrals.  The importance of developing fast methods for                       integrating well behaved, accurately known, functions is                        highlighted by observing that this is the main obstacle in the                  way of the creation of a general Bayesian statistical analysis                  software package.  In this project, the simulation approach to                  numerical integration will be investigated.  A taxonomy of                      manufacturing system models will also be developed.                                  This is a multidiscipliary research project in statistical                 modeling and stochastic simulation and their use in manufacturing               systems design and evaluation.  The proposed research program is                composed of three distinct, but related, types of projects:                     statistical problems in simulation, statistical and computational               problems involving simulation, and evaluation of statistical and                simulation procedures for analyzing manufacturing models.  The                  objective is to develop and refine computational statistics and                 simulation methodology, with particular emphasis on evaluation                  and comparison of methods in the context of manufacturing                       systems.  The significance of the research is the development of                mathematics and algorithms in computational statistics and                      stochastic simulation that are relevant to practitioners of                     statistics and simulation, especially in the manufacturing                      setting.
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[{'Code': '1269', 'Text': 'STATISTICS'}, {'Code': '1271', 'Text': 'COMPUTATIONAL MATHEMATICS'}, {'Code': '1454', 'Text': 'SYSTEMS THEORY'}, {'Code': '1463', 'Text': 'INTEGRATION ENGINEERING'}, {'Code': '5514', 'Text': 'OPERATIONS RESEARCH'}]
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