Mark E. Johnson
ABSTRACT
The statistics profession has been remiss in exploiting the numerous advances in simulation methodology. The purpose of this article is to outline progress in variate generation relevant to the conduct of statistical simulation studies. The emphasis is on multivariate distributions, a thriving area of research.
- Beckman, R. J. and M. E. Johnson (1987). "Fitting Student's t Distribution to Grouped Data, With Application to a Particle Scattering Experiment," Technometrics, to appear. Google Scholar
Digital Library
- Cambanls,S., S. Huang, and G. Simons (1981). "On the Theory of Elliptically Contoured Distributions,"Journal of Multivariate analysis, 11, 368-385.Google ScholarCross Ref
- Chase, G. R. and W. G. Bulgren (1971). "A Monte Carlo Investigation of the Robustness of Hofelling's T2 ,"Journal of the American Statistical Association, 66, 499-502.Google Scholar
- Conover, W. J., M. E. Johnson and M. M. Johnson (1981). "A Comparative Study of Tests for Bomogeneity of Variances, vith Applications to the Outer Continential Shelf Bidding Data," Technometrlcs, 23, 351-361.Google ScholarCross Ref
- Devlin, S. J., R. Gnanadesikan, and J. R. Kettenring (1981). "Robust Estimation of Dispersion Matrices and Principle Components," Journal of the American Statistical Association, 76, 354- 362.Google ScholarCross Ref
- Devroye, L. (1986). Non-Uniform Random Variate Generation. Springer-Verlag~ New York.Google Scholar
- Efron, B. (1977)o "Bootstrap Nethods: Another Look at the Jacknife," Annals of Statistics, 7, 1-26.Google Scholar
- Hopkins, J. W. and P. P. F. Clay (1963). "Some Empirical Distributions of Bivariate T2 and Homoscedastlclty Crlterlor H Under Unegual Variance and Leptokurtosis," Journal of the American Statictical Association, 58, 1048-1053.Google Scholar
- Johnson, M. E. (1987). Multivariate Statistical Simulation, John Wiley, New York. Google ScholarDigital Library
- Johnson, M. E., C. L. Tietjen, and R. J. Beckman (1980). "A New Family of Probability Distributions and Applications to Monte Carlo Studies," Journal of the American Statistical Association, 75, 276-279.Google ScholarCross Ref
- Nachtsheim, C. J. and M. E. Johnson (1986). "Some New Anisotropic Distributions Useful in Simulation," in preparation.Google Scholar
Index Terms
- Distribution selection in statistical simulation studies
Recommendations
A multi-criterion evaluation approach to selection of the best statistical distribution
Using traditional statistical analysis methods one chooses a hypothesized distribution to describe the observed data, estimate the distribution parameters, and then apply the Kolmogorov-Smirnov test statistic Dmax or the Chi-square test statistic χ2 to ...
Correcting statistical models via empirical distribution functions
We consider the two-sample homogeneity problem where the information contained in two samples is used to test the equality of the underlying distributions. In cases where one sample is simulated by a procedure modelling the data generating process of ...
Generating Survival Data in the Simulation Studies of Cox Model
ICIC '10: Proceedings of the 2010 Third International Conference on Information and Computing - Volume 04The Cox proportional hazards regression (Cox model) is commonly used to model survival data as a function of covariates. Simulation studies, which use computer intensive procedures to assess the performance of a variety of statistical methods, are ...
Comments