1. Criterion to Determine the Sample Size in Stochastic Simulation Processes.
- Author
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Molina-Muñoz, Juan Daniel and Christen, José Andrés
- Subjects
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STOCHASTIC processes , *MARKOV chain Monte Carlo , *SAMPLE size (Statistics) , *MONTE Carlo method , *STOCHASTIC integrals - Abstract
Objective: To propose a criterion to determine the sample size in stochastic simulations of MC (Monte Carlo) and MCMC (Markov chain Monte Carlo), guaranteeing certain precision estimating parameters. It is intended that the accuracy is guaranteed in a dimensionless way. Materials and methods: This paper proposes a criterion is proposed that seeks to meet the stated objective. In addition, a methodology for its application. Results and discussion: The application of the methodology is presented in 3 different contexts: MC simulation in which the sample of interest presents moderate variability, MC simulation in which the sample of interest presents excessive variability, and MCMC simulation. In all cases, adequate estimates of the number of MC and MCMC runs are obtained from relatively small samples. Furthermore, the application of the methodology represents only a marginal additional computational cost. Conclusions: The criterion presented in this paper allows for determining the sample size in stochastic simulations, guaranteeing dimensionless precision in estimating parameters. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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