IDEAS home Printed from https://ideas.repec.org/a/jss/jstsof/v009i04.html
   My bibliography  Save this article

Simulating Correlated Multivariate Pseudorandom Numbers

Author

Listed:
  • Al-Subaihi, Ali A.

Abstract

A modification of the Kaiser and Dichman (1962) procedure of generating multivariate random numbers with specified intercorrelation is proposed. The procedure works with positive and non-positive definite population correlation matrix. A SAS module is also provided to run the procedure.

Suggested Citation

  • Al-Subaihi, Ali A., 2004. "Simulating Correlated Multivariate Pseudorandom Numbers," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 9(i04).
  • Handle: RePEc:jss:jstsof:v:009:i04
    DOI: http://hdl.handle.net/10.18637/jss.v009.i04
    as

    Download full text from publisher

    File URL: https://www.jstatsoft.org/index.php/jss/article/view/v009i04/paper-2.pdf
    Download Restriction: no

    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v009i04/Multivariate_Data_Generation.sas.txt
    Download Restriction: no

    File URL: https://libkey.io/http://hdl.handle.net/10.18637/jss.v009.i04?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Allen Fleishman, 1978. "A method for simulating non-normal distributions," Psychometrika, Springer;The Psychometric Society, vol. 43(4), pages 521-532, December.
    2. C. Vale & Vincent Maurelli, 1983. "Simulating multivariate nonnormal distributions," Psychometrika, Springer;The Psychometric Society, vol. 48(3), pages 465-471, September.
    3. Pandu Tadikamalla, 1980. "On simulating non-normal distributions," Psychometrika, Springer;The Psychometric Society, vol. 45(2), pages 273-279, June.
    4. Todd Headrick & Shlomo Sawilowsky, 1999. "Simulating correlated multivariate nonnormal distributions: Extending the fleishman power method," Psychometrika, Springer;The Psychometric Society, vol. 64(2), pages 251-251, June.
    5. Todd Headrick & Shlomo Sawilowsky, 1999. "Simulating correlated multivariate nonnormal distributions: Extending the fleishman power method," Psychometrika, Springer;The Psychometric Society, vol. 64(1), pages 25-35, March.
    6. Henry Kaiser & Kern Dickman, 1962. "Sample and population score matrices and sample correlation matrices from an arbitrary population correlation matrix," Psychometrika, Springer;The Psychometric Society, vol. 27(2), pages 179-182, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mishra, SK, 2004. "On generating correlated random variables with a given valid or invalid Correlation matrix," MPRA Paper 1782, University Library of Munich, Germany.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gary van Vuuren & Riaan de Jongh, 2017. "A comparison of risk aggregation estimates using copulas and Fleishman distributions," Applied Economics, Taylor & Francis Journals, vol. 49(17), pages 1715-1731, April.
    2. Max Auerswald & Morten Moshagen, 2015. "Generating Correlated, Non-normally Distributed Data Using a Non-linear Structural Model," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 920-937, December.
    3. Ke-Hai Yuan & Peter Bentler, 2002. "On robusiness of the normal-theory based asymptotic distributions of three reliability coefficient estimates," Psychometrika, Springer;The Psychometric Society, vol. 67(2), pages 251-259, June.
    4. Mohan D. Pant & Todd C. Headrick, 2017. "Simulating Uniform- and Triangular- Based Double Power Method Distributions," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 6(1), pages 1-1.
    5. M Hashem Pesaran & Takashi Yamagata, 2012. "Testing CAPM with a Large Number of Assets," Discussion Papers 12/05, Department of Economics, University of York.
    6. Beasley, T. Mark & Zumbo, Bruno D., 2003. "Comparison of aligned Friedman rank and parametric methods for testing interactions in split-plot designs," Computational Statistics & Data Analysis, Elsevier, vol. 42(4), pages 569-593, April.
    7. Pesaran, M. H. & Yamagata, T., 2012. "Testing CAPM with a Large Number of Assets (Updated 28th March 2012)," Cambridge Working Papers in Economics 1210, Faculty of Economics, University of Cambridge.
    8. Yen Lee & David Kaplan, 2018. "Generating Multivariate Ordinal Data via Entropy Principles," Psychometrika, Springer;The Psychometric Society, vol. 83(1), pages 156-181, March.
    9. Headrick, Todd C. & Mugdadi, Abdel, 2006. "On simulating multivariate non-normal distributions from the generalized lambda distribution," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 3343-3353, July.
    10. M. Hashem Pesaran & Takashi Yamagata, 2017. "Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities," Discussion Papers 17/04, Department of Economics, University of York.
    11. Njål Foldnes & Steffen Grønneberg, 2015. "How General is the Vale–Maurelli Simulation Approach?," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 1066-1083, December.
    12. Headrick, Todd C., 2002. "Fast fifth-order polynomial transforms for generating univariate and multivariate nonnormal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 40(4), pages 685-711, October.
    13. Nagahara, Yuichi, 2004. "A method of simulating multivariate nonnormal distributions by the Pearson distribution system and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 47(1), pages 1-29, August.
    14. Emanuela Raffinetti & Pier Alda Ferrari, 2021. "A dependence measure flow tree through Monte Carlo simulations," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(2), pages 467-496, April.
    15. Emanuela Raffinetti & Pier Alda Ferrari, 0. "A dependence measure flow tree through Monte Carlo simulations," Quality & Quantity: International Journal of Methodology, Springer, vol. 0, pages 1-30.
    16. Jeff Jones & Niels Waller, 2015. "The Normal-Theory and Asymptotic Distribution-Free (ADF) Covariance Matrix of Standardized Regression Coefficients: Theoretical Extensions and Finite Sample Behavior," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 365-378, June.
    17. Hakan Demirtas, 2016. "A Note on the Relationship Between the Phi Coefficient and the Tetrachoric Correlation Under Nonnormal Underlying Distributions," The American Statistician, Taylor & Francis Journals, vol. 70(2), pages 143-148, May.
    18. Reinartz, Werner & Haenlein, Michael & Henseler, Jörg, 2009. "An empirical comparison of the efficacy of covariance-based and variance-based SEM," International Journal of Research in Marketing, Elsevier, vol. 26(4), pages 332-344.
    19. Headrick, Todd C. & Sheng, Yanyan & Hodis, Flaviu-Adrian, 2007. "Numerical Computing and Graphics for the Power Method Transformation Using Mathematica," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 19(i03).
    20. Mahul, Olivier, 2002. "Hedging Price Risk in the Presence of Crop Yield and Revenue Insurance," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24881, European Association of Agricultural Economists.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jss:jstsof:v:009:i04. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.jstatsoft.org/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum (email available below). General contact details of provider: http://www.jstatsoft.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.