Journal of Applied Probability

The logarithmic skew-normal distributions are moment-indeterminate

Lin Gwo Dong and Stoyanov Jordan

Source: J. Appl. Probab. Volume 46, Number 3 (2009), 909-916.

Abstract

We study the class of logarithmic skew-normal (LSN) distributions. They have heavy tails; however, all their moments of positive integer orders are finite. We are interested in the problem of moments for such distributions. We show that the LSN distributions are all nonunique (moment-indeterminate). Moreover, we explicitly describe Stieltjes classes for some LSN distributions; they are families of infinitely many distributions, which are different but have the same moment sequence as a fixed LSN distribution.

Primary Subjects: 60E05
Secondary Subjects: 44A60
Keywords: Logarithmic skew-normal distribution; heavy tail; finite moments; problem of moments; nonuniqueness; Stieltjes class

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Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.jap/1253279858
Digital Object Identifier: doi:10.1239/jap/1253279858
Zentralblatt MATH identifier: 05611424

References

Akhiezer, N. I. (1965). The Classical Moment Problem and Some Related Questions in Analysis. Hafner Publishing, New York.
Mathematical Reviews (MathSciNet): MR184042
Zentralblatt MATH: 0135.33803
Arnold, B. C. and Beaver, R. J. (2000). Hidden truncation models. Sankhyā A 62, 23--35.
Mathematical Reviews (MathSciNet): MR1769732
Arnold, B. C. and Lin, G. D. (2004). Characterizations of the skew-normal and generalized chi distributions. Sankhyā 66, 593--606.
Mathematical Reviews (MathSciNet): MR2205811
Azzalini, A. (1985). A class of distributions which includes the normal ones. Scand. J. Statist. 12, 171--178.
Mathematical Reviews (MathSciNet): MR808153
Azzalini, A., Dal Cappello, T. and Kotz, S. (2003). Log-skew-normal and log-skew-$t$ distributions as models for family income data. J. Income Distribution 11, 12--20.
Azzalini, A. and Dalla Valle, A. (1996). The multivariate skew-normal distribution. Biometrika 83, 715--726.
Mathematical Reviews (MathSciNet): MR1440039
Zentralblatt MATH: 0885.62062
Digital Object Identifier: doi:10.1093/biomet/83.4.715
Chai, H. S. and Bailey, K. R. (2008). Use of log-skew-normal distribution in analysis of continuous data with a discrete component at zero. Statist. Med. 27, 3643--3655.
Gradshteyn, I. S. and Ryzhik, I. M. (2000). Tables of Integrals, Series, and Products, 6th edn. Academic Press, San Diego, CA.
Mathematical Reviews (MathSciNet): MR1773820
Henze, N. (1986). A probabilistic representation of the `skew-normal' distribution. Scand. J. Statist. 13, 271--275.
Mathematical Reviews (MathSciNet): MR886466
Heyde, C. C. (1963). On a property of the lognormal distribution. J. R. Statist. Soc. B 25, 392--393.
Mathematical Reviews (MathSciNet): MR171336
Lin, G. D. (1997). On the moment problems. Statist. Prob. Lett. 35, 85--90. (Correction: 50 (2000), 205.)
Mathematical Reviews (MathSciNet): MR1467713
O'Hagan, A. and Leonard, T. (1976). Bayes estimation subject to uncertainty about parameter constraints. Biometrika 63, 201--203.
Mathematical Reviews (MathSciNet): MR428571
Zentralblatt MATH: 0326.62025
Digital Object Identifier: doi:10.1093/biomet/63.1.201
Pakes, A., Hung, W.-L. and Wu, J.-W. (2001). Criteria for the unique determination of probability distributions by moments. Austral. N. Z. J. Statist. 43, 101--111.
Mathematical Reviews (MathSciNet): MR1837499
Schmoyeri, R. L., Beauchamp, J. J., Brandt, C. C. and Hoffman, F. O. Jr. (1996). Difficulties with the lognormal model in mean estimation and testing. Environm. Ecol. Statist. 3, 81--97.
Slud, E. V. (1993). The moment problem for polynomial forms in normal random variables. Ann. Prob. 21, 2200--2214.
Mathematical Reviews (MathSciNet): MR1245307
Zentralblatt MATH: 0788.60028
Digital Object Identifier: doi:10.1214/aop/1176989017
Project Euclid: euclid.aop/1176989017
Stieltjes, T. J. (1894). Recherches sur les fractions continues. Ann. Fac. Sci. Univ. Toulouse 8, J1--J122 and 9 (1895), A5--A47. Reprinted in: Ann. Fac. Sci. Univ. Toulouse (6) 4 (1995), A5--A47.
Mathematical Reviews (MathSciNet): MR1623484
Stoyanov, J. (1997). Counterexamples in Probability, 2nd edn. John Wiley, Chichester.
Mathematical Reviews (MathSciNet): MR930671
Stoyanov, J. (2000). Krein condition in probabilistic moment problems. Bernoulli 6, 939--949.
Mathematical Reviews (MathSciNet): MR1791909
Digital Object Identifier: doi:10.2307/3318763
Project Euclid: euclid.bj/1081282696
Stoyanov, J. (2004). Stieltjes classes for moment-indeterminate probability distributions. In Stochastic Methods and Their Applications (J. Appl. Prob. Spec. Vol. 41A), eds J. Gani and E. Seneta, Applied Probability Trust, Sheffield, pp. 281--294.
Mathematical Reviews (MathSciNet): MR2057580
Zentralblatt MATH: 1070.60012
Digital Object Identifier: doi:10.1239/jap/1082552205
Project Euclid: euclid.jap/1082552205
Stoyanov, J. and Tolmatz, L. (2005). Method for constructing Stieltjes classes for M-indeterminate probability distributions. Appl. Math. Comput. 165, 669--685.
Mathematical Reviews (MathSciNet): MR2138909
Zentralblatt MATH: 1069.60016
Digital Object Identifier: doi:10.1016/j.amc.2004.04.035
Williamson, M. and Gaston, K. J. (2005). The lognormal distribution is not an appropriate null hypothesis for the species-abundance distribution. J. Animal Ecology 74, 409--422.
Yamazaki, H. and Lueck, R. (1990). Why oceanic dissipation rates are not lognormal? J. Phys. Oceanography 20, 1907--1918.

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