## Abstract

The Central Limit Theorem (CLT) and Extreme Value Theory (EVT) study, respectively, the stochastic limit-laws of sums and maxima of sequences of independent and identically distributed (i.i.d.) random variables via an affine scaling scheme. In this research we study the stochastic limit-laws of populations of i.i.d. random variables via nonlinear scaling schemes. The stochastic population-limits obtained are fractal Poisson processes which are statistically self-similar with respect to the scaling scheme applied, and which are characterized by two elemental structures: (i) a universal power-law structure common to all limits, and independent of the scaling scheme applied; (ii) a specific structure contingent on the scaling scheme applied. The sum-projection and the maximum-projection of the population-limits obtained are generalizations of the classic CLT and EVT results - extending them from affine to general nonlinear scaling schemes.

Original language | English |
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Pages (from-to) | 4985-4996 |

Number of pages | 12 |

Journal | Physica A: Statistical Mechanics and its Applications |

Volume | 387 |

Issue number | 21 |

DOIs | |

State | Published - 1 Sep 2008 |

## Keywords

- Central Limit Theorem (CLT)
- Extreme Value Theory (EVT)
- Fractal Poisson processes
- Nonlinear scaling
- Power-laws
- Self-similarity
- Stochastic limit-laws