IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v71y2014icp955-970.html
   My bibliography  Save this article

Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R

Author

Listed:
  • Asquith, William H.

Abstract

The implementation characteristics of two method of L-moments (MLM) algorithms for parameter estimation of the 4-parameter Asymmetric Exponential Power (AEP4) distribution are studied using the R environment for statistical computing. The objective is to validate the algorithms for general application of the AEP4 using R. An algorithm was introduced in the original study of the L-moments for the AEP4. A second or alternative algorithm is shown to have a larger L-moment-parameter domain than the original. The alternative algorithm is shown to provide reliable parameter production and recovery of L-moments from fitted parameters. A proposal is made for AEP4 implementation in conjunction with the 4-parameter Kappa distribution to create a mixed-distribution framework encompassing the joint L-skew and L-kurtosis domains. The example application provides a demonstration of pertinent algorithms with L-moment statistics and two 4-parameter distributions (AEP4 and the Generalized Lambda) for MLM fitting to a modestly asymmetric and heavy-tailed dataset using R.

Suggested Citation

  • Asquith, William H., 2014. "Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 955-970.
  • Handle: RePEc:eee:csdana:v:71:y:2014:i:c:p:955-970
    DOI: 10.1016/j.csda.2012.12.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947312004471
    Download Restriction: Full text for ScienceDirect subscribers only.

    File URL: https://libkey.io/10.1016/j.csda.2012.12.013?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Giulio Bottazzi & Angelo Secchi, 2011. "A new class of asymmetric exponential power densities with applications to economics and finance," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 20(4), pages 991-1030, August.
    2. Sean Holly & Ivan Petrella & Emiliano Santoro, 2013. "Aggregate fluctuations and the cross-sectional dynamics of firm growth," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 459-479, February.
    3. Karvanen, Juha & Nuutinen, Arto, 2008. "Characterizing the generalized lambda distribution by L-moments," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1971-1983, January.
    4. Zhu, Dongming & Zinde-Walsh, Victoria, 2009. "Properties and estimation of asymmetric exponential power distribution," Journal of Econometrics, Elsevier, vol. 148(1), pages 86-99, January.
    5. Saralees Nadarajah & Mahdi Teimouri, 2012. "On the Characteristic Function for Asymmetric Exponential Power Distributions," Econometric Reviews, Taylor & Francis Journals, vol. 31(4), pages 475-481.
    6. Elamir, Elsayed A. H. & Seheult, Allan H., 2003. "Trimmed L-moments," Computational Statistics & Data Analysis, Elsevier, vol. 43(3), pages 299-314, July.
    7. Asquith, William H., 2007. "L-moments and TL-moments of the generalized lambda distribution," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4484-4496, May.
    8. Serfling, Robert & Xiao, Peng, 2007. "A contribution to multivariate L-moments: L-comoment matrices," Journal of Multivariate Analysis, Elsevier, vol. 98(9), pages 1765-1781, October.
    9. Delicado, P. & Goria, M.N., 2008. "A small sample comparison of maximum likelihood, moments and L-moments methods for the asymmetric exponential power distribution," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1661-1673, January.
    10. Karvanen, Juha, 2006. "Estimation of quantile mixtures via L-moments and trimmed L-moments," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 947-959, November.
    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. Camilo Lillo & Víctor Leiva & Orietta Nicolis & Robert G. Aykroyd, 2018. "L-moments of the Birnbaum–Saunders distribution and its extreme value version: estimation, goodness of fit and application to earthquake data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(2), pages 187-209, January.
    2. Torsten Heinrich & Jangho Yang & Shuanping Dai, 2020. "Growth, development, and structural change at the firmlevel: The example of the PR China," Chemnitz Economic Papers 040, Department of Economics, Chemnitz University of Technology.
    3. Lafond, François & Farmer, J. Doyne & Koutroumpis, Pantelis & Winkler, Julian & Heinrich, Torsten & Yang, Jangho, 2019. "Measuring productivity dispersion: a parametric approach using the Lévy alpha-stable distribution," INET Oxford Working Papers 2019-14, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.

    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. Karvanen, Juha & Nuutinen, Arto, 2008. "Characterizing the generalized lambda distribution by L-moments," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1971-1983, January.
    2. Tata Subba Rao & Granville Tunnicliffe Wilson & Andrew Harvey & Rutger-Jan Lange, 2017. "Volatility Modeling with a Generalized t Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 175-190, March.
    3. Delicado, P. & Goria, M.N., 2008. "A small sample comparison of maximum likelihood, moments and L-moments methods for the asymmetric exponential power distribution," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1661-1673, January.
    4. Emmanuel Jurczenko & Bertrand Maillet & Paul Merlin, 2008. "Efficient Frontier for Robust Higher-order Moment Portfolio Selection," Post-Print halshs-00336475, HAL.
    5. Steve Su, 2016. "Flexible modelling of survival curves for censored data," Journal of Statistical Distributions and Applications, Springer, vol. 3(1), pages 1-20, December.
    6. Reiner Franke, 2015. "How Fat-Tailed is US Output Growth?," Metroeconomica, Wiley Blackwell, vol. 66(2), pages 213-242, May.
    7. Gourieroux, C. & Jasiak, J., 2008. "Dynamic quantile models," Journal of Econometrics, Elsevier, vol. 147(1), pages 198-205, November.
    8. Huber, Peter & Oberhofer, Harald & Pfaffermayr, Michael, 2017. "Who creates jobs? Econometric modeling and evidence for Austrian firm level data," European Economic Review, Elsevier, vol. 91(C), pages 57-71.
    9. Darolles, Serge & Gourieroux, Christian & Jasiak, Joann, 2009. "L-performance with an application to hedge funds," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 671-685, September.
    10. Chalabi, Yohan / Y. & Scott, David J & Wuertz, Diethelm, 2012. "An asymmetry-steepness parameterization of the generalized lambda distribution," MPRA Paper 37814, University Library of Munich, Germany.
    11. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.
    12. Su, Steve, 2009. "Confidence intervals for quantiles using generalized lambda distributions," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3324-3333, July.
    13. Fabrizio Leisen & Luca Rossini & Cristiano Villa, 2020. "Loss-based approach to two-piece location-scale distributions with applications to dependent data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(2), pages 309-333, June.
    14. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," Economics Letters, Elsevier, vol. 179(C), pages 29-32.
    15. Liu, Xiaochun, 2019. "On tail fatness of macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 62(C).
    16. Lafond, François & Farmer, J. Doyne & Koutroumpis, Pantelis & Winkler, Julian & Heinrich, Torsten & Yang, Jangho, 2019. "Measuring productivity dispersion: a parametric approach using the Lévy alpha-stable distribution," INET Oxford Working Papers 2019-14, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    17. Di Nardo, E. & Guarino, G. & Senato, D., 2008. "Symbolic computation of moments of sampling distributions," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 4909-4922, July.
    18. Vitezić Vanja & Srhoj Stjepan & Perić Marko, 2018. "Investigating Industry Dynamics in a Recessionary Transition Economy," South East European Journal of Economics and Business, Sciendo, vol. 13(1), pages 43-67, June.
    19. Halvarsson, Daniel, 2019. "Asymmetric Double Pareto Distributions: Maximum Likelihood Estimation with Application to the Growth Rate Distribution of Firms," Ratio Working Papers 327, The Ratio Institute.
    20. Nadarajah, Saralees & Chan, Stephen & Afuecheta, Emmanuel, 2013. "On the characteristic function for asymmetric Student t distributions," Economics Letters, Elsevier, vol. 121(2), pages 271-274.

    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:eee:csdana:v:71:y:2014:i:c:p:955-970. See general information about how to correct material in RePEc.

    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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.