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A Generalized-Alpha–Beta-Skew Normal Distribution with Applications

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Abstract

Recently there is a lot of research related to skewed distributions and their growing relevance in data analytics. In the present work we introduce a new generalized version of alpha beta skew normal distribution and some of its basic properties are investigated. Some extensions of the proposed distribution have also been studied. A simulation study has been conducted to see the performance of the obtained estimators of the parameters using Metropolis–Hastings (MH) algorithm. The appropriateness of the proposed distribution has been tested by comparing it with twelve closely related and nested distributions using Akaike Information Criterion. The Likelihood Ratio test has been employed for testing the relevance of the induction of the additional parameters in the proposed model.

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References

  1. Olson DL, Shi Y, Shi Y (2007) Introduction to business data mining (Vol. 10, pp. 2250–2254). New York: McGraw-Hill/Irwin

  2. Shi Y, Tian Y, Kou G, Peng Y, Li J (2011) Optimization based data mining: theory and applications. Springer

  3. Tien JM (2017) Internet of things, real-time decision making, and artificial intelligence. Ann Data Sci 4(2):149–178

    Article  Google Scholar 

  4. Cormode G, Muthukrishnan S (2005) Summarizing and mining skewed data streams. In: Proceedings of the 2005 SIAM international conference on data mining. Society for Industrial and Applied Mathematics, pp 44–55

  5. Manning W (2012) Dealing with skewed data on costs and expenditures. In: The Elgar companion to health economics, 2nd Edition. Edward Elgar Publishing

  6. Theodossiou P (1998) Financial data and the skewed generalized t distribution. Manag Sci 44(12-part-1):1650–1661

    Article  Google Scholar 

  7. Juárez MA, Steel MF (2010) Model-based clustering of non-Gaussian panel data based on skew-t distributions. J Bus Econ Stat 28(1):52–66

    Article  Google Scholar 

  8. Gao J, Fan W, Han J, Yu PS (2007) A general framework for mining concept-drifting data streams with skewed distributions. In: Proceedings of the 2007 SIAM international conference on data mining. Society for Industrial and Applied Mathematics, pp 3–14

  9. Hammel I, Lagunoff D, Bauza M, Chi E (1983) Periodic, multimodal distribution of granule volumes in mast cells. Cell Tissue Res 228(1):51–59

    Article  Google Scholar 

  10. Dimitrov B, JrD G, Chukova S (1997) Probability distributions in periodic random environment and their applications. SIAM J Appl Math 57(2):501–517

    Article  Google Scholar 

  11. Sinha RK (2012) A thought on exotic statistical distributions. World Acad Sci Eng Technol 61:366–369

    Google Scholar 

  12. Chakraborty S, Hazarika PJ (2011) A survey of the theoretical developments in univariate skew normal distributions. Assam Stat Rev 25(1):41–63

    Google Scholar 

  13. Chakraborty S, Hazarika PJ, Ali MM (2015) A multimodal skewed extension of normal distribution: its properties and applications. Statistics 49(4):859–877

    Article  Google Scholar 

  14. Shah S, Hazarika PJ, Chakraborty S, Ali MM (2020) The Log-Balakrishnan-alpha-skew-normal distribution and its applications. Pak J Stat Oper Res 16(1):109–117

    Article  Google Scholar 

  15. Shah S, Hazarika PJ, Chakraborty S (2020) A new alpha skew laplace distribution: properties and its applications. Int J Agric Stat Sci 16(1):1–10

    Google Scholar 

  16. Shah S, Chakraborty S, Hazarika PJ (2020) The Balakrishnan alpha skew logistic distribution: properties and applications. Int J Appl Math Stat 59(1):76–92

    Google Scholar 

  17. Azzalini A (1985) A class of distributions which includes the normal ones. Scand J Statist 12:171–178

    Google Scholar 

  18. Elal-Olivero D (2010) Alpha-skew-normal distribution. Proyecciones (Antofagasta) 29(3):224–240

    Article  Google Scholar 

  19. Shafiei S, Doostparast M, Jamalizadeh A (2016) The alpha–beta skew normal distribution: properties and applications. Statistics 50(2):338–349

    Google Scholar 

  20. Venegas O, Bolfarine H, Gallardo DI, Vergara-Fernández A, Gómez HW (2016) A note on the log alpha skew normal model with geochemical applications. Appl Math 10(5):1697–1703

    Google Scholar 

  21. Sharafi M, Sajjadnia Z, Behboodian J (2017) A new generalization of alpha-skew-normal distribution. Commun Stat Theory Methods 46(12):6098–6111

    Article  Google Scholar 

  22. Hazarika PJ, Shah S, Chakraborty S (2020) Balakrishnan alpha skew normal distribution: properties and applications. Malaysian J Sci 39(2):71–91

    Article  Google Scholar 

  23. Henze N (1986) A probabilistic representation of the skew normal distribution. Scand J Statist 13:271–275

    Google Scholar 

  24. Chib S, Greenberg E (1995) Understanding the metropolis-hastings algorithm. Am Stat 49(4):327–335

    Google Scholar 

  25. Cook RD, Weisberg S (1994) Transforming a response variable for linearity. Biometrika 81(4):731–737

    Article  Google Scholar 

  26. Xiang Y, Gubian S, Suomela B, Hoeng J (2013) Generalized simulated annealing for global optimization: the GenSA package. R J 5(1):13–28

    Article  Google Scholar 

  27. Wahed A, Ali MM (2001) The skew-logistic distribution. J Stat Res 35(2):71–80

    Google Scholar 

  28. Nekoukhou V, Alamatsaz MH (2012) A family of skew-symmetric-Laplace distributions. Stat Pap 53(3):685–696

    Article  Google Scholar 

  29. Harandi SS, Alamatsaz MH (2013) Alpha–Skew–Laplace distribution. Stat Probab Lett 83(3):774–782

    Article  Google Scholar 

  30. Hazarika PJ, Chakraborty S (2014) Alpha-skew-logistic distribution. IOSR. J Math 10(4):36–46

    Google Scholar 

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Acknowledgements

The authors would like to thank the editor and reviewers for their suggestions which led to this improved version.

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Correspondence to Partha Jyoti Hazarika.

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Appendix

Appendix

1.1 Derivation of normalizing constant \(C(\alpha ,\beta ,\lambda )\)

$$\begin{aligned} C(\alpha ,\beta ,\lambda ) & = \int\limits_{ - \infty }^{\infty } {[(1 - \alpha \,z - \beta \,z^{3} )^{2} + 1]\varphi (z)\,\Phi (\lambda \,z)} \,dz \\ & = \int\limits_{ - \infty }^{\infty } {(2 - 2\alpha \,z + \alpha^{2} z^{2} - 2\beta \,z^{3} + 2\alpha \beta \,z^{4} + \beta^{2} z^{6} )\varphi (z)\,\Phi (\lambda \,z)} \,dz \\ & = \int\limits_{ - \infty }^{\infty } {\varphi (z;\lambda )\,} \,dz - \alpha \,E(Z_{\lambda } ) + \frac{{\alpha^{2} }}{2}E(Z_{\lambda }^{2} ) - \beta \,E(Z_{\lambda }^{3} ) + \alpha \beta \,E(Z_{\lambda }^{4} ) + \frac{{\beta^{2} }}{2}\,E(Z_{\lambda }^{6} ) \\ & = 1 + \frac{{\alpha^{2} }}{2} + 3\,\alpha \,\beta + \frac{{15\beta^{2} }}{2} - \alpha \sqrt {\frac{2}{\pi }} \frac{\lambda }{{\sqrt {1 + \lambda^{2} } }} - \beta \sqrt {\frac{2}{\pi }} \frac{\lambda }{{\sqrt {1 + \lambda^{2} } }}\frac{{3 + 2\lambda^{2} }}{{1 + \lambda^{2} }} \\ & = 1 + 3\,\alpha \,\beta - \alpha \,b\delta - \beta \,b\delta \frac{{3 + 2\lambda^{2} }}{{1 + \lambda^{2} }} + \frac{{\alpha^{2} }}{2} + \frac{{15\beta^{2} }}{2}, \\ \end{aligned}$$

where \(b = \sqrt {\frac{2}{\pi }} ,\,\,\delta = \frac{\lambda }{{\sqrt {1 + \lambda^{2} } }}\) and \(\varphi (z;\lambda )\) is the density function of \(Z_{\lambda } \sim SN(\lambda )\).

1.2 Derivation of the cdf

$$\begin{aligned} F_{Z} (z) & = P(Z \le z)\, = \int\limits_{ - \infty }^{z} {\frac{{(1 - \alpha \,t - \beta \,t^{3} )^{2} + 1}}{C(\alpha ,\beta ,\lambda )}} \,\varphi (t)\,\Phi (\lambda t)dt \\ & = \frac{1}{C(\alpha ,\beta ,\lambda )}\int\limits_{ - \infty }^{z} {(2 - 2\alpha \,t + \alpha^{2} t^{2} - 2\beta \,t^{3} + 2\alpha \beta \,t^{4} + \beta^{2} t^{6} )\varphi (t)\,\Phi (\lambda t)dt} \\ & = \frac{1}{C(\alpha ,\beta ,\lambda )}\left[ {\int\limits_{ - \infty }^{z} {2\varphi (t)\,\Phi (\lambda t)dt} \, - 2\alpha \int\limits_{ - \infty }^{z} {t\varphi (t)\,\Phi (\lambda t)dt} \, + \alpha^{2} \int\limits_{ - \infty }^{z} {t^{2} \varphi (t)\,\Phi (\lambda t)dt} \, - 2\beta \int\limits_{ - \infty }^{z} {t^{3} \varphi (t)\,\Phi (\lambda t)dt} \, + } \right. \\ & \left. {\quad 2\alpha \beta \int\limits_{ - \infty }^{z} {t^{4} \varphi (t)\,\Phi (\lambda t)dt} \, + \beta^{2} \int\limits_{ - \infty }^{z} {t^{6} \varphi (t)\,\Phi (\lambda t)dt} } \right] \\ \end{aligned}$$

Putting the above following results we get the desired result.

$$\begin{aligned} \int\limits_{ - \infty }^{z} {2\varphi (t)\,\Phi (\lambda t)dt} & = \Phi (z;\lambda ),\int\limits_{ - \infty }^{z} {t\varphi (t)\,\Phi (\lambda t)dt} = - \varphi (z)\,\Phi (\lambda z) + \frac{{\lambda \,Erf\left( {(z\sqrt {1 + \lambda^{2} } )/\sqrt 2 } \right)}}{{2\sqrt {2\pi } \sqrt {1 + \lambda^{2} } }} \\ \int\limits_{ - \infty }^{z} {t^{2} \varphi (t)\,\Phi (\lambda t)dt} & = - z\varphi (z)\,\Phi (\lambda z) + \frac{{b\,\delta \,\varphi \left( {z\sqrt {1 + \lambda^{2} } } \right)}}{{2\sqrt {1 + \lambda^{2} } }}, \\ \int\limits_{ - \infty }^{z} {t^{3} \varphi (t)\,\Phi (\lambda t)dt} & = - (2 + z^{2} )\varphi (z)\,\Phi (\lambda z) + \frac{{\lambda \,Erf\left( {(z\sqrt {1 + \lambda^{2} } )/\sqrt 2 } \right)}}{{\sqrt {2\pi } \sqrt {1 + \lambda^{2} } }} - z\frac{{b\,\delta \,\varphi \left( {z\sqrt {1 + \lambda^{2} } } \right)}}{{2\sqrt {1 + \lambda^{2} } }} + \frac{{b\,\delta \,\Phi \left( {z\sqrt {1 + \lambda^{2} } } \right)}}{{2\sqrt {1 + \lambda^{2} } }}, \\ \int\limits_{ - \infty }^{z} {t^{4} \varphi (t)\,\Phi (\lambda t)dt} & = - z(3 + z^{2} )\varphi (z)\,\Phi (\lambda z) - \frac{{b\,\delta \,\varphi \left( {z\sqrt {1 + \lambda^{2} } } \right)\,\left( {5 + z^{2} + \lambda^{2} (3 + z^{2} )} \right)}}{{2\left( {\sqrt {1 + \lambda^{2} } } \right)^{3} }} + \frac{3}{2}\Phi (z;\lambda ), \\ \int\limits_{ - \infty }^{z} {t^{6} \varphi (t)\,\Phi (\lambda t)dt} & = - z(15 + 5z^{2} + z^{4} )\varphi (z)\,\Phi (\lambda z) + \frac{15}{2}\Phi (z;\lambda ) + \\ & \quad \frac{{b\,\delta \,\varphi \left( {z\sqrt {1 + \lambda^{2} } } \right)\,\left( { - 33 - 40\lambda^{2} - 15\lambda^{4} - z^{4} (1 + \lambda^{2} )^{2} - z^{2} (9 + 14\lambda^{2} + 5\lambda^{4} )} \right)}}{{2\left( {\sqrt {1 + \lambda^{2} } } \right)^{5} }}. \\ \end{aligned}$$

1.3 Derivation of the moment

$$\begin{aligned} E(Z^{k} ) & = \int\limits_{ - \infty }^{\infty } {z^{k} \frac{{(1 - \alpha z - \beta z^{3} )^{2} + 1}}{C(\alpha ,\beta ,\lambda )}\varphi (z)\,\Phi (\lambda z)\,} dz \\ & = \frac{1}{C(\alpha ,\beta ,\lambda )}\left[ {\int\limits_{ - \infty }^{\infty } {\,2\,z^{k} } \,\varphi (z)\,\Phi (\lambda z)dz - 2\alpha \int\limits_{ - \infty }^{\infty } {\,z^{k + 1} } \varphi (z)\,\Phi (\lambda z)\,dz + \alpha^{2} \int\limits_{ - \infty }^{\infty } {\,z^{k + 2} } \varphi (z)\,\Phi (\lambda z)\,dz - } \right. \\ & \left. {\quad 2\beta \int\limits_{ - \infty }^{\infty } {\,z^{k + 3} } \varphi (z)\,\Phi (\lambda z)\,dz + 2\alpha \beta \int\limits_{ - \infty }^{\infty } {\,z^{k + 4} } \varphi (z)\,\Phi (\lambda z)\,dz + \beta^{2} \int\limits_{ - \infty }^{\infty } {\,z^{k + 6} } \varphi (z)\,\Phi (\lambda z)\,dz} \right] \\ & = \frac{1}{C(\alpha ,\beta ,\lambda )}\left[ {E(Z_{\lambda }^{k} ) - 2\alpha \,E(Z_{\lambda }^{k + 1} ) + \alpha^{2} \,E(Z_{\lambda }^{k + 2} ) - 2\beta \,E(Z_{\lambda }^{k + 3} ) + 2\alpha \beta \,E(Z_{\lambda }^{k + 4} ) + \beta^{2} \,E(Z_{\lambda }^{k + 5} )} \right] \\ \end{aligned}$$

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Shah, S., Hazarika, P.J., Chakraborty, S. et al. A Generalized-Alpha–Beta-Skew Normal Distribution with Applications. Ann. Data. Sci. 10, 1127–1155 (2023). https://doi.org/10.1007/s40745-021-00325-0

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