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On the Folded Normal Distribution

Author

Listed:
  • Michail Tsagris

    (School of Mathematical Sciences, University of Nottingham, NG7 2RD, UK)

  • Christina Beneki

    (School of Business and Economics, TEI of Ionian Islands, 31100 Lefkada, Greece)

  • Hossein Hassani

    (Statistical Research Centre, Executive Business Centre, Bournemouth University, BH8 8EB, UK)

Abstract

The characteristic function of the folded normal distribution and its moment function are derived. The entropy of the folded normal distribution and the Kullback–Leibler from the normal and half normal distributions are approximated using Taylor series. The accuracy of the results are also assessed using different criteria. The maximum likelihood estimates and confidence intervals for the parameters are obtained using the asymptotic theory and bootstrap method. The coverage of the confidence intervals is also examined.

Suggested Citation

  • Michail Tsagris & Christina Beneki & Hossein Hassani, 2014. "On the Folded Normal Distribution," Mathematics, MDPI, vol. 2(1), pages 1-17, February.
    • Handle: RePEc:gam:jmathe:v:2:y:2014:i:1:p:12-28:d:32965
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    References listed on IDEAS

    as
    1. Psarakis, Stelios & Panaretos, John, 1990. "The Folded t Distribution," MPRA Paper 6257, University Library of Munich, Germany.
    2. Psarakis, Stelios & Panaretos, John, 2001. "On Some Bivariate Extensions of the Folded Normal and the Folded-T Distributions," MPRA Paper 6383, University Library of Munich, Germany.
    3. Yee, Thomas W., 2010. "The VGAM Package for Categorical Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i10).
    Full references (including those not matched with items on IDEAS)

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    Cited by:

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    More about this item

    Keywords

    folded normal distribution; entropy; Kullback–Leibler; maximum likelihood estimates;
    All these keywords.

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions

    Statistics

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