Erratum to "A method of simulating multivariate nonnormal distributions by the Pearson distribution system and estimation" [Comput. Statist. Data Anal. 47 (2004) 1-29] (DOI:10.1016/j.csda.2003.10.008);A method of simulating multivariate nonnormal distributions by the Pearson distribution system and estimation

Computational Statistics and Data Analysis

Volumn 47, Issue 1, 2004, Pages 1-29

  Nagahara, Yuichi ^a  

^a MEIJI UNIVERSITY   (Japan)

Author keywords

Generator of random numbers; Multivariate nonnormal distributions; Pearson distribution system; Skewness and kurtosis; Third and fourth order moment matrix

Indexed keywords

APPROXIMATION THEORY; CURVE FITTING; MATRIX ALGEBRA; MAXIMUM LIKELIHOOD ESTIMATION; MULTIVARIABLE CONTROL SYSTEMS; STATISTICAL METHODS;

GENERATOR OF RANDOM NUMBERS; KURTOSIS; MOMENT MATRIX; MULTIVARIATE NONNORMAL DISTRIBUTIONS; PEARSON DISTRIBUTION SYSTEM; SKEWNESS;

COMPUTATIONAL METHODS;

EID: 4544350377     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2005.04.001     Document Type: Erratum

References (32)

1. Azzalini A., Valle A.D. The multivariate skew-normal distribution. Biometrika. 83:1996;715-726.
2. Bonett D.G., Seier E. A test of normality with high uniform power. Comput. Statist. Data Anal. 40:2002;435-445.
3. Devroye L. A simple algorithm for generating random variates with a log-concave density. Computing. 33:1984;247-257.
4. Devroye L. Non-Uniform Random Variate Generation. 1986;Springer, New York.
5. Doornik J.A., O'Brien R.J. Numerically stable cointegration analysis. Comput. Statist. Data Anal. 41:2002;185-193.
6. Elderton W.P., Johnson N.L. Systems of Frequency Curves. 1969;Cambridge University Press, Cambridge.
7. Fang K.-T., Kotz S., Ng K.W. Symmetric Multivariate and Related Distributions. 1990;Chapman & Hall, London.
8. Fleishmann A. A method for simulating non-normal distributions. Psychometrika. 43:1978;521-532.
9. Headrick T.C. Fast fifth-order polynomial transforms for generating univariate and multivariate nonnormal distributions. Comput. Statist. Data Anal. 40:2002;685-711.
10. Hoadley A.B. Use of the Pearson densities for approximating a skew density whose left terminal and first three moments are known. Biometrika. 55:(3):1968;559-563.
11. Johnson N.L., Kotz S., Balakrishnan N. Continuous Univariate Distributions - 1. 2nd Edition :1994;Wiley, New York.
12. Kotz, S., Nagahara, Y., 2001. On the characteristic function of Pearson type IV distribution. Research Memorandum, No. 790, Institute of Statistical Mathematics.
13. Matsumoto M., Nishimura T. Mersenne twister a 623-dimensionally equidistributed uniform pseudorandom number generator. ACM Trans. Model. Comput. Simul. 8:1998;3-30.
14. McGrath, E.J., Irving, D.C., 1973. Techniques for efficient Monte Carlo simulation: volume 2: random number generation for selected probability distributions. Technical Report SAI-72-590-LJ, Science Applications, Inc., La Jolla, CA.
15. Nagahara Y. The PDF and CF of Pearson type IV distributions and the ML estimation of the parameters. Statist. Probab. Lett. 43:1999;251-264.
16. Nagahara, Y., 2003. Non-Gaussian filter and smoother based on the Pearson distribution system. J. Time Ser. Anal., forthcoming.
17. Ord J.K. Families of Frequency Distributions. 1972;Griffin, London.
18. Parrish R. On an integrated approach to member selection and parameter estimation for Pearson distributions. Comput. Statist. Data Anal. 1:1983;239-255.
19. Pearson E.S. Some problems arising in approximating to probability distributions, using moments. Biometrika. 50:1963;95-111.
20. Pearson K. Memoir on skew variation in homogeneous material. Philos. Trans. Roy. Soc. A. 186:1895;343-414.
21. Pearson K. Tables for Statisticians and Biometricians, 1. 1914;Cambridge University Press, Cambridge.
22. Pearson E.S., Hartrey H.O. Biometrika Tables for Statisticians, 1. 1954;Cambridge University Press, Cambridge.
23. Press W., et al. Numerical Recipes in Fortran 77. 1992;Cambridge University Press, Cambridge.
24. Shorack G.R. Probability for Statisticians. 2000;Springer, New York.
25. Stuart, A., Ord, J.K., 1994. Kendall's Advanced Theory of Statistics, Vol. 1. Distribution Theory, 6th Edition Edward Arnold, London.
26. Tadikamalla P.R. On simulating non-normal distributions. Psychometrika. 45:1980;273-279.
27. Vale D., Maurelli V.A. Simulating multivariate nonnormal distributions. Psychometrika. 48:1983;465-471.
28. Wilcox R.R. Inferences based on multiple skipped correlations. Comput. Statist. & Data Anal. 44:2003;223-236.
29. Yuan K.-H., Bentler P.M. Generating multivariate distributions with specified marginal skewness and kurtosis. Bandilla W., Faulbaum F. SoftStat'97-Advances in Statistical Software 6. 1997;385-391 Lucius & Lucius, Stuttgart, Germany.
30. Yuan K.-H., Bentler P.M. On normal theory and associated test statistics in covariance structure analysis under two classes of nonnormal distributions. Statist. Sinica. 9:1999;831-853.
31. Yuan K.-H., Bentler P.M. On asymptotic distributions of normal theory MLE in covariance structure analysis under some nonnormal distributions. Statist. Probab. Lett. 42:1999;107-113.
32. Yuan K.-H., Bentler P.M. Inferences on correlation coefficients in some classes of nonnormal distributions. J. Multivariate Anal. 72:2000;230-248.