Contains articles, reports and new research about Lunar Simulations. New scientific data returned by a number of orbiter and landed missions to the Moon have renewed a strong interest in the worldwide community for lunar exploration.
Three methods for generating outcomes on multivariate normal random vectors with a specified variance-covariance matrix are presented. A comparison is made to determine which method requires the least computer execution time and memory space when utilizing the IBM 360/67. All methods use as a basis a standard Gaussian random number generator. Results of the comparison indicate that the method based on triangular factorization of the covariance matrix generally requires less memory space and computer time than the other two method