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What is the official name of this distribution, $$k\exp(-\lambda|x|^\alpha),$$ where $\alpha$ is usually less than 1, but greater than 0? More importantly, could anyone tell me what the variance of this distribution is? Thank you very much.


(Edit: Oct 7 '13 at 21:37) Thank you all.

This distribution can be called generalized normal distribution, whose standard form is

$$f(x)=\beta/2\alpha\Gamma(1/\beta)\exp(-|(x-\mu)/\alpha|^\beta)$$

whose variance is $$\alpha^2 \Gamma(3/\beta)/\Gamma(1/\beta)$$

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  • $\begingroup$ This looks like some kind of "Generalized Laplace Distribution" $\endgroup$
    – Suvrit
    Commented Oct 7, 2013 at 14:35
  • $\begingroup$ stretched exponential distribution; oh, and the p-th moment is $\lambda^{-p/\alpha} \Gamma[(1+p)/\alpha]/\Gamma[1/\alpha]$ $\endgroup$ Commented Oct 7, 2013 at 14:44
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    $\begingroup$ Your notation for the 'generalised Normal' parameter $\alpha$ clashes with that of the original question ... which will cause much confusion to all. $\endgroup$
    – wolfies
    Commented Nov 7, 2013 at 17:57

2 Answers 2

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While Nadarajah (2005) may have used the term 'generalised Normal' to describe a density that nests this form, there are more suitable names that extend far further back in time, and which accordingly seem much more appropriate.

In particular, I believe this should properly be referred to as a Subbotin distribution (Subbotin 1923). Other later references include:

  • Diananda (1949)

  • Turner (1960)

  • Zeckhauser and Thompson (1970)

  • McDonald and Newey (1988)

  • Mineo and Ruggieri (2005)

The functional form given by Subbotin (1923) defines the pdf as:

$$f(x) = \frac{\alpha }{2 b \Gamma \left(\frac{1}{\alpha }\right)}\text{exp}\left[-\left|\frac{x}{b}\right|^{\alpha }\right]$$

Subbotin used parameter $b = 1/h$, but the functional form is otherwise identical to that given here. In this form: $$Var(X) = \frac{b^2 \Gamma \left(\frac{3}{\alpha}\right)}{\Gamma \left(\frac{1}{\alpha}\right)}$$

Here is a plot of the pdf with $b=2$, as parameter $\alpha>1$ varies:

(source)

and again for parameter $0<\alpha<1$:

(source)

Other names include: Box-Tiao distribution (McDonald and Newey 1988), and Power-Exponential (McDonald and Newey 1988, Johnson et al. 1995). Finally, it is worth noting that some economic papers inappropriately ascribe the name 'Subbotin distribution' to an Exponential-Power distribution that has a different functional form.

References

  • Subbotin, M.T. (1923), On the law of frequency of error, Matematicheskii Sbornik, 31, 296-301.

  • Diananda, P. H. (1949), Note on some properties of maximum likelihood estimates, Proceedings of the Cambridge Philosophical Society, 45, 536-544.

  • Turner, M. E. (1960), On heuristic estimation methods, Biometrics, 16(2), 299-301.

  • Zeckhauser, R. and Thompson, M. (1970), Linear regression with non-normal error terms, The Review of Economics and Statistics, 52, 280-286.

  • McDonald, J. B. and Newey, W. K. (1988), Partially adaptive estimation of regression models via the generalized t distribution, Econometric Theory, 4, 428-457.

  • Mineo, A. M. and Ruggieri, M. (2005), A software tool for the Exponential Power distribution: the normalp package, Journal of Statistical Software, 12(4), 1-21.

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  • $\begingroup$ Does anyone know how to program the subbotin distribution in Mathematica or how to get the parameter alpha for empirical data? Thanks! $\endgroup$ Commented Jan 8, 2017 at 0:48
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According to Maple, the variance is $$ \dfrac{\sqrt{3}\; 27^{1/\alpha}}{6\pi} \Gamma\left(\dfrac{3+\alpha}{3\alpha}\right) \Gamma\left(\dfrac{3+2\alpha}{3\alpha}\right) \lambda^{-2/\alpha} $$

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