39,806 research outputs found

    A decorated tree approach to random permutations in substitution-closed classes

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    We establish a novel bijective encoding that represents permutations as forests of decorated (or enriched) trees. This allows us to prove local convergence of uniform random permutations from substitution-closed classes satisfying a criticality constraint. It also enables us to reprove and strengthen permuton limits for these classes in a new way, that uses a semi-local version of Aldous' skeleton decomposition for size-constrained Galton--Watson trees.Comment: New version including referee's corrections, accepted for publication in Electronic Journal of Probabilit

    Optimal path and cycle decompositions of dense quasirandom graphs

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    Motivated by longstanding conjectures regarding decompositions of graphs into paths and cycles, we prove the following optimal decomposition results for random graphs. Let 0<p<10<p<1 be constant and let GGn,pG\sim G_{n,p}. Let odd(G)odd(G) be the number of odd degree vertices in GG. Then a.a.s. the following hold: (i) GG can be decomposed into Δ(G)/2\lfloor\Delta(G)/2\rfloor cycles and a matching of size odd(G)/2odd(G)/2. (ii) GG can be decomposed into max{odd(G)/2,Δ(G)/2}\max\{odd(G)/2,\lceil\Delta(G)/2\rceil\} paths. (iii) GG can be decomposed into Δ(G)/2\lceil\Delta(G)/2\rceil linear forests. Each of these bounds is best possible. We actually derive (i)--(iii) from `quasirandom' versions of our results. In that context, we also determine the edge chromatic number of a given dense quasirandom graph of even order. For all these results, our main tool is a result on Hamilton decompositions of robust expanders by K\"uhn and Osthus.Comment: Some typos from the first version have been correcte

    Risk bounds for purely uniformly random forests

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    Random forests, introduced by Leo Breiman in 2001, are a very effective statistical method. The complex mechanism of the method makes theoretical analysis difficult. Therefore, a simplified version of random forests, called purely random forests, which can be theoretically handled more easily, has been considered. In this paper we introduce a variant of this kind of random forests, that we call purely uniformly random forests. In the context of regression problems with a one-dimensional predictor space, we show that both random trees and random forests reach minimax rate of convergence. In addition, we prove that compared to random trees, random forests improve accuracy by reducing the estimator variance by a factor of three fourths

    Growth of the Brownian forest

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    Trees in Brownian excursions have been studied since the late 1980s. Forests in excursions of Brownian motion above its past minimum are a natural extension of this notion. In this paper we study a forest-valued Markov process which describes the growth of the Brownian forest. The key result is a composition rule for binary Galton--Watson forests with i.i.d. exponential branch lengths. We give elementary proofs of this composition rule and explain how it is intimately linked with Williams' decomposition for Brownian motion with drift.Comment: Published at http://dx.doi.org/10.1214/009117905000000422 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Schnyder decompositions for regular plane graphs and application to drawing

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    Schnyder woods are decompositions of simple triangulations into three edge-disjoint spanning trees crossing each other in a specific way. In this article, we define a generalization of Schnyder woods to dd-angulations (plane graphs with faces of degree dd) for all d3d\geq 3. A \emph{Schnyder decomposition} is a set of dd spanning forests crossing each other in a specific way, and such that each internal edge is part of exactly d2d-2 of the spanning forests. We show that a Schnyder decomposition exists if and only if the girth of the dd-angulation is dd. As in the case of Schnyder woods (d=3d=3), there are alternative formulations in terms of orientations ("fractional" orientations when d5d\geq 5) and in terms of corner-labellings. Moreover, the set of Schnyder decompositions on a fixed dd-angulation of girth dd is a distributive lattice. We also show that the structures dual to Schnyder decompositions (on dd-regular plane graphs of mincut dd rooted at a vertex vv^*) are decompositions into dd spanning trees rooted at vv^* such that each edge not incident to vv^* is used in opposite directions by two trees. Additionally, for even values of dd, we show that a subclass of Schnyder decompositions, which are called even, enjoy additional properties that yield a reduced formulation; in the case d=4, these correspond to well-studied structures on simple quadrangulations (2-orientations and partitions into 2 spanning trees). In the case d=4, the dual of even Schnyder decompositions yields (planar) orthogonal and straight-line drawing algorithms. For a 4-regular plane graph GG of mincut 4 with nn vertices plus a marked vertex vv, the vertices of G\vG\backslash v are placed on a (n1)×(n1)(n-1) \times (n-1) grid according to a permutation pattern, and in the orthogonal drawing each of the 2n22n-2 edges of G\vG\backslash v has exactly one bend. Embedding also the marked vertex vv is doable at the cost of two additional rows and columns and 8 additional bends for the 4 edges incident to vv. We propose a further compaction step for the drawing algorithm and show that the obtained grid-size is strongly concentrated around 25n/32×25n/3225n/32\times 25n/32 for a uniformly random instance with nn vertices
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