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SIMULATION INPUT MODELING

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Mind Map on SIMULATION INPUT MODELING, created by Luis Montes on 28/10/2015.
Luis Montes
Mind Map by Luis Montes, updated more than 1 year ago
Luis Montes
Created by Luis Montes over 9 years ago
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SIMULATION INPUT MODELING
  1. Successful input modeling requires a close match between the input model and the true underlying probabilistic mechanism associated with the system.
    1. COLLECTING DATA
      1. The first is the classical approach, where a designed experiment is conducted to collect the data.
        1. The second is the exploratory approach, where questions are addressed by means of existing data that the modeler had no hand in collecting.
          1. there are several things that can be “wrong” about the data set
            1. Wrong amount of aggregation.
              1. Wrong distribution in time.
                1. Wrong distribution in space.
                  1. Censored data.
                    1. Insufficient distribution resolution.
                  2. Input models
                    1. assessing independence.
                      1. autocorrelation
                        1. analysis of this data set includes plotting a histogram and calculating the values of some sample statistics
                          1. to be determined is whether a parametric or nonparametric model should be chosen for the process
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