On Box–Muller Transformation and Simulation of Normal Record Data

N. Balakrishnan*, H. Y. So, X. J. Zhu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


Record data are commonly encountered in many fields such as sports, geography, finance, and reliability. In this article, we use the well-known Box–Muller transformation to develop an efficient method of simulating record data from the normal distribution. Another method based on exponential records is also discussed. Then, the performance of these algorithms is compared with some standard simulation methods.

Original languageEnglish
Pages (from-to)3670-3682
Number of pages13
JournalCommunications in Statistics: Simulation and Computation
Issue number10
Publication statusPublished - 25 Nov 2016
Externally publishedYes


  • Best linear unbiased estimates
  • Box–Muller algorithm
  • Kolmogorov–Smirnov test
  • Lower records
  • Upper records
  • Variance-covariance matrix

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