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| 01531cam 2200253za 4500 |
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| 001 | 9.829481 |
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| 003 | CaOODSP |
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| 005 | 20221107145310 |
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| 007 | cr ||||||||||| |
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| 008 | 170104s2014 oncd |o f|0| 0 eng d |
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| 040 | |aCaOODSP|beng |
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| 043 | |an-cn--- |
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| 086 | 1 |aD69-19/2014E-PDF |
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| 245 | 00|aStatistical validation of a new Python-based military workforce simulation model |h[electronic resource] / |cStephen Okazawa ... [et al.]. |
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| 260 | |a[Ottawa] : |bDefence Research and Development Canada, |c[2014] |
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| 300 | |a[10] p. : |bcharts. |
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| 500 | |a"DRDC-RDDC-2014-P48." |
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| 504 | |aIncludes bibliographic references. |
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| 520 | 3 |a"In this paper, we demonstrate the use of nonparametric and time series statistical techniques to test the hypothesis that the results obtained from Arena-based and Python-based implementations of the same military rank structure model are equivalent. Important measures of system performance that were tested include population size, time in rank, promotions, releases and course qualifications. This methodology will be of broad use to analytics practitioners who face the challenge of testing whether two independently-developed simulation models of the same system are in fact statistically equivalent"--Abstract. |
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| 692 | 07|2gccst|aTechnical reports |
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| 692 | 07|2gccst|aMilitary technology |
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| 700 | 1 |aOkazawa, Stephen. |
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| 710 | 1 |aCanada. |bDefence R&D Canada. |
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| 856 | 40|qPDF|s650 KB|uhttps://publications.gc.ca/collections/collection_2017/rddc-drdc/D69-19-2014-eng.pdf |
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