QUASI-MONTE CARLO METHODS FOR COMPUTATION OF MULTIDIMENSIONAL INTEGRALS RELATED TO BAYESIAN MODELS IN INTERNATIONAL MIGRATION FORECASTING
QUASI-MONTE CARLO METHODS FOR COMPUTATION OF MULTIDIMENSIONAL INTEGRALS RELATED TO BAYESIAN MODELS IN INTERNATIONAL MIGRATION FORECASTING
DOI:
https://doi.org/10.46687/jsar.v13i1.233Keywords:
Quasi-Monte Carlo sequences, multidimensional integrals, Hammersley sequence, Fibonacci lattice rule, Faure sequence, international migration forecasting, Bayesian statisticsAbstract
The paper addresses selected methodological aspects of international migration forecasting. The new methods based on the Bayesian statistics have been recently developed. A fundamental problem in Bayesian statistics is the accurate evaluation of multidimensional integrals. A comprehensive experimental study based on Faure and Hammersley low discrepancy sequences and Fibonacci based lattice rule has been done. The numerical tests show that the stochastic algorithms under consideration are efficient tool for computing multidimensional integrals. It is important in order to obtain a more accurate and reliable interpretation of the results in Bayesian statistics which is a foundation in international migration forecasting.
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