Hostname: page-component-848d4c4894-jbqgn Total loading time: 0 Render date: 2024-06-22T04:41:37.943Z Has data issue: false hasContentIssue false

Tails of Stopped Random Products: The Factoid and Some Relatives

Published online by Cambridge University Press:  14 July 2016

Anthony G. Pakes*
Affiliation:
University of Western Australia
*
Postal address: School of Mathematics and Statistics, University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia. Email address: pakes@maths.uwa.edu.au
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The upper tail behaviour is explored for a stopped random product ∏j=1NXj, where the factors are positive and independent and identically distributed, and N is the first time one of the factors occupies a subset of the positive reals. This structure is motivated by a heavy-tailed analogue of the factorial n!, called the factoid of n. Properties of the factoid suggested by computer explorations are shown to be valid. Two topics about the determination of the Zipf exponent in the rank-size law for city sizes are discussed.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 2008 

References

Adler, R. J., Feldman, R. E. and Taqqu, S. (eds) (1998). A Practical Guide to Heavy Tails. Birkhauser, Boston, MA.Google Scholar
Albin, J. M. P. (2008). A note on the closure of convolution power mixtures (random sums) of exponential distributions. J. Austral. Math. Soc. 84, 17.CrossRefGoogle Scholar
Asmussen, S. (2003). Applied Probability and Queues, 2nd edn. Springer, New York.Google Scholar
Bingham, N. H., Goldie, C. M. and Teugels, J. L. (1987). Regular Variation. Cambridge University Press.CrossRefGoogle Scholar
Cline, D. B. H. (1987). Convolutions of distributions with exponential and subexponential tails. J. Austral. Math. Soc. Ser. A 43, 347356. (Correction: 48, (1990), 152–153.)CrossRefGoogle Scholar
Daley, D. J. and Vere-Jones, D. (1988). An Introduction to the Theory of Point Processes. Springer, New York.Google Scholar
Derman, C. (1955). Some contributions to the theory of denumerable Markov chains. Trans. Amer. Math. Soc. 79, 541555.CrossRefGoogle Scholar
Feller, W. (1971). An Introduction to Probability Theory and Its Applications, Vol. 2, 2nd edn. John Wiley, New York.Google Scholar
Foss, S. and Korshunov, D. (2007). Lower limits and equivalences for convolution tails. Ann. Prob. 35, 366383.CrossRefGoogle Scholar
Gabaix, X. (1999). Zipf's law for cities: an explanation. Quart. J. Econom. 114, 739767.CrossRefGoogle Scholar
Gnedenko, B. V. and Korolev, V. Y.} (1996). Random Summation: Limit Theorems and Applications. CRC Press, Boca Raton, FL.Google Scholar
Hardy, G. H. (1901). On the Frullanian integral ∫0 (ɸ({ ax}m)-ɸ({ bx}m))(log x)p x{-1}dx. Quart. J. Math. 33, 113144.Google Scholar
Harrison, J. M. (1985). Brownian Motion and Stochastic Flow Systems. John Wiley, New York.Google Scholar
Hayes, B. (2007a). Fat tails. Amer. Scientist 95, 200204.CrossRefGoogle Scholar
Hayes, B. (2007b). Web log. http://bit-player.org.Google Scholar
Jeffreys, H. and Jeffreys, B. S. (1962). Methods of Mathematical Physics. Cambridge University Press.Google Scholar
Kalashnikov, V. V. (1997). Geometric Sums: Bounds for Rare Events with Applications. Kluwer, Dordrecht.CrossRefGoogle Scholar
Korshunov, D. (1997). On the distribution tail of the maximum of a random walk. Stoch. Processes Appl. 72, 97103.CrossRefGoogle Scholar
Meyn, S. and Tweedie, R. L. (1993). Markov Chains and Stochastic Stability. Springer, London.CrossRefGoogle Scholar
Mitzenmacher, M. (2004). A brief history of generative models for power law and lognormal distributions. Internet Math. 1, 226251.CrossRefGoogle Scholar
Newman, M. E. J. (2005). Power laws, Pareto distributions and Zipf's law. Contemp. Phys. 46, 323351.CrossRefGoogle Scholar
Pakes, A. G. (2004). Convolution equivalence and infinite divisibility. J. Appl. Prob. 41, 407424.CrossRefGoogle Scholar
Pakes, A. G. (2007). Convolution equivalence and infinite divisibility: corrections and corollaries. J. Appl. Prob. 44, 294304.CrossRefGoogle Scholar
Rachev, S. (ed.) (2003). Handbook of Heavy Tailed Distributions in Finance. Elsevier, Amsterdam.Google Scholar
Ramachandran, B. and Lau, K. S. (1991). Functional Equations in Probability Theory. Academic Press, San Diego.Google Scholar
Reed, W. J. and Hughes, B. D. (2002). From gene families and genera to incomes and internet file sizes: Why power laws are so common in nature. Phys. Rev. E 66, 067103, 4 pp.CrossRefGoogle ScholarPubMed
Revuz, D. and Yor, M. (1991). Continuous Martingales and Brownian Motion. Springer, Berlin.CrossRefGoogle Scholar
Rudin, W. (1974). Real and Complex Analysis, 2nd. edn. McGraw-Hill, New York.Google Scholar
Watanabe, T. (2008). Convolution equivalence and distributions of random sums. Prob. Theory Relat. Fields 142, 367397.CrossRefGoogle Scholar