2020
DOI: 10.1016/j.disc.2020.111995
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Pattern distributions in Dyck paths with a first return decomposition constrained by height

Abstract: We consider the system of equations A k (x) = p(x)A k−1 (x)(q(x) + k i=0 Ai(x)) for k r + 1 where Ai(x), 0 i r, are some given functions and show how to obtain a close form for A(x) = k 0 A k (x). We apply this general result to the enumeration of certain subsets of Dyck, Motzkin, skew Dyck, and skew Motzkin paths, defined recursively according to the first return decomposition with a monotonically non-increasing condition relative to the maximal ordinate reached by an occurrence of a given pattern π.

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Cited by 5 publications
(5 citation statements)
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“…. , C i+1 )) = P , where P is the path described as This function is a bijection, where the inverse function is given by decomposing a path by using the following algorithm: Algorithm 1 Inverse function φ (or reverse) (1) If there are (−1)-valleys, go to step (2). If there are no consecutive valleys with difference equal to −1, then the path is increasing and can be decomposed by using only pyramids ∆ and λ in the following way:…”
Section: Number Of D-dyck Paths and Peaks Statisticmentioning
confidence: 99%
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“…. , C i+1 )) = P , where P is the path described as This function is a bijection, where the inverse function is given by decomposing a path by using the following algorithm: Algorithm 1 Inverse function φ (or reverse) (1) If there are (−1)-valleys, go to step (2). If there are no consecutive valleys with difference equal to −1, then the path is increasing and can be decomposed by using only pyramids ∆ and λ in the following way:…”
Section: Number Of D-dyck Paths and Peaks Statisticmentioning
confidence: 99%
“…. , n − 1} there is exactly one path in Q n of the form (XY ) i (XY ) n−i , where its area is equal to i 2 + (n − i) 2 . So, the total area of these types of paths is…”
Section: The Area Of the (−1)-dyck Pathsmentioning
confidence: 99%
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“…For n ě 1, we denote by n the constant statistic returning the value n. The popularity of a pattern p in S is the total number of occurrences of p over all objects of S, that is ppSq " ř aPS ppaq ( [6,9,10]). Let S 1 be a set of combinatorial objects, we say that two statistics, s on S and t on S 1 , have the same distribution if there exists a bijection f : S Ñ S 1 satisfying spaq " tpf paqq for any a P S. In this case, with a slight abuse of the notation already used in [5], we write f psq " t or s " t whenever f is the identity.…”
Section: Introduction and Notationsmentioning
confidence: 99%
“…We say that two statistics s ∈ T A and t ∈ T B have the same distribution, or are equidistributed, if there exists a bijection f : A → B such that s(a) = t(f (a)) for any a ∈ A. In this case, with a slight abuse of the notation already used in [4], we write shortly f (s) = t or s = t whenever f is the identity.…”
Section: Introductionmentioning
confidence: 99%