The hierarchical Bayesian model of gold production in Malaysia

Nora Muda, Norashikin Ramli

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Malaysia is a country which is rich in natural resources and one of it is gold. Gold has become an important national commodity. This study focused on gold production in Malaysia and also in 102 countries from 1995 to 2010. The Hierarchical Bayesian Model is selected to determine and explained the scenario of gold production in Malaysia. Through the analysis of hierarchical Bayesian model of the cumulative gold production in Malaysia and other countries for 15 years, the posterior mean of gold production in 102 countries are determined. Variance Partition Coefficient (VPC) is also calculated to quantify percentage of total variation in world gold production attributable to between countries variation. This study has found that the posterior mean for Malaysia and world gold production in hierarchical Bayesian are 3646 kg and 24 180 kg respectively. VPC reading obtained is 0.9226 which indicates that 93%of the total variations were contributed by variation between countries. This shows that the variation of gold production between countries is large and also the correlation of gold production within countries is high.

Original languageEnglish
Article number70639
JournalIndian Journal of Science and Technology
Volume8
Issue number12
Publication statusPublished - 1 Jun 2015

Fingerprint

Hierarchical Bayesian model
Malaysia
Coefficients
Scenarios
Commodities
Natural resources

Keywords

  • Gold
  • Posterior mean
  • Total variation
  • Variance partition coefficient
  • World gold productionyears

ASJC Scopus subject areas

  • General

Cite this

The hierarchical Bayesian model of gold production in Malaysia. / Muda, Nora; Ramli, Norashikin.

In: Indian Journal of Science and Technology, Vol. 8, No. 12, 70639, 01.06.2015.

Research output: Contribution to journalArticle

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