Abstract

Combinatorics We provide a rather general asymptotic scheme for combinatorial parameters that asymptotically follow a discrete double-exponential distribution. It is based on analysing generating functions Gh(z) whose dominant singularities converge to a certain value at an exponential rate. This behaviour is typically found by means of a bootstrapping approach. Our scheme is illustrated by a number of classical and new examples, such as the longest run in words or compositions, patterns in Dyck and Motzkin paths, or the maximum degree in planted plane trees.

Highlights

  • One encounters the situation that one obtains a sequence of generating functions Gh(z), depending on a parameter h whose distribution is to be studied, such that the dominant singularity ζh of Gh converges to a value ζ as h → ∞, and ζh − ζ decreases exponentially with h

  • Remark 4 The conditions are quite natural for combinatorial applications, but it is possible to modify them in various ways

  • Thereafter, we consider a variety of combinatorial examples to which this general asymptotic scheme can be applied

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Summary

Introduction

One encounters the situation that one obtains a sequence of generating functions Gh(z), depending on a parameter h whose distribution is to be studied, such that the dominant singularity ζh of Gh converges to a value ζ as h → ∞, and ζh − ζ decreases exponentially with h. The archetypical example is probably the distribution of the longest sequence of 1’s in a random 0-1-sequence: Let Gh(z) denote the generating function for 0-1-sequences with the property that there is no sequence of more than h consecutive 1’s. Behaviour in the dominant singularity typically leads to a discrete limit law analogous to the Gumbel distribution, and to periodic fluctuations. Remark 4 The conditions are quite natural for combinatorial applications, but it is possible to modify them in various ways (e.g., by allowing further terms in the asymptotic expansions with exponents between α and α + 1, with additional assumptions on the coefficients.) Proofs of these two theorems are provided . Thereafter, we consider a variety of combinatorial examples to which this general asymptotic scheme can be applied

Proof of the main results
A special case
Words and digital expansions
Compositions
Geometric random variables
Conclusion

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