Journal article
Extreme value estimation for a function of a random sample using binomial moments scheme and Boolean functions of events
Discrete Applied Mathematics, v 219, pp 210-218
11 Mar 2017
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We propose a novel optimization model to find reliable bounds of a real valued function of a simple random sample from a population. If the sample size is n, then the function would be a function of n i.i.d. random variables (by simple random sampling). Comprehensive evaluation by simulation is challenging when the function is asymmetric, requiring a large number of simulations for desired statistical precision. The proposed model is based on the binomial moments to construct a systematic mathematical form, and is further developed by utilizing Boolean logic. Numerical examples are presented.
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Details
- Title
- Extreme value estimation for a function of a random sample using binomial moments scheme and Boolean functions of events
- Creators
- Jinwook Lee - Drexel UniversityJongpil Kim - Rutgers, The State University of New JerseyAndrás Prékopa - RUTCOR (Center for Operations Research), Rutgers University, Piscataway, NJ 08854, United States
- Publication Details
- Discrete Applied Mathematics, v 219, pp 210-218
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000393265700021
- Scopus ID
- 2-s2.0-85008214642
- Other Identifier
- 991019168491404721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Mathematics, Applied