Javascript must be enabled to continue!
A new combinatorial representation of the additive coalescent
View through CrossRef
AbstractThe standard additive coalescent starting with n particles is a Markov process which owns several combinatorial representations, one by Pitman as a process of coalescent forests, and one by Chassaing and Louchard as the block sizes in a parking scheme. In the coalescent forest representation, edges are added successively between a random node and a random root. In this paper, we investigate an alternative construction by, instead, adding edges between roots. This construction induces exactly the same process in terms of cluster sizes, meanwhile, it allows us to make numerous new connections with other combinatorial and probabilistic models: size biased percolation, parking scheme in a tree, increasing trees, random cuts of trees. The variety of the combinatorial objects involved justifies our interest in this construction.
Title: A new combinatorial representation of the additive coalescent
Description:
AbstractThe standard additive coalescent starting with n particles is a Markov process which owns several combinatorial representations, one by Pitman as a process of coalescent forests, and one by Chassaing and Louchard as the block sizes in a parking scheme.
In the coalescent forest representation, edges are added successively between a random node and a random root.
In this paper, we investigate an alternative construction by, instead, adding edges between roots.
This construction induces exactly the same process in terms of cluster sizes, meanwhile, it allows us to make numerous new connections with other combinatorial and probabilistic models: size biased percolation, parking scheme in a tree, increasing trees, random cuts of trees.
The variety of the combinatorial objects involved justifies our interest in this construction.
Related Results
The Validity of the Coalescent Approximation for Large Samples
The Validity of the Coalescent Approximation for Large Samples
Abstract
The Kingman coalescent, widely used in genetics, is known to be a good approximation when the sample size is small relative to the popul...
Robust Design for Coalescent Model Inference
Robust Design for Coalescent Model Inference
Abstract
—The coalescent process describes how changes in the size of a population influence the genealogical patterns of sequences sampled from that population. Th...
Linkage Analysis and Coalescents
Linkage Analysis and Coalescents
Abstract
I’he number of chapters in this volume, and in the research literature generally, that discuss the coalescent attests to the importance of this concept, bot...
Morphological constraints on cerebellar granule cell combinatorial diversity
Morphological constraints on cerebellar granule cell combinatorial diversity
Abstract
Combinatorial expansion by the cerebellar granule cell layer (GCL) is fundamental to theories of cerebellar contributions to motor control and learning. Gr...
The Coalescent With Gene Conversion
The Coalescent With Gene Conversion
Abstract
In this article we develop a coalescent model with intralocus gene conversion. The distribution of the tract length is geometric in concordance with results...
Unveiling the Environmental and Economic Implications of Additive Manufacturing on Inbound Transportation
Unveiling the Environmental and Economic Implications of Additive Manufacturing on Inbound Transportation
This studyaims to investigate the impact of additive manufacturing (AM) on the sustainability of inbound transportation. By combining insights from existing litera...
Estimation of additive and dominance genetic variance components for female fertility traits in Iranian Holstein cows
Estimation of additive and dominance genetic variance components for female fertility traits in Iranian Holstein cows
AbstractThe aim of the current study was to estimate additive and dominance genetic variance components for days from calving to first service (DFS), a number of services to concep...
The interaction between neural populations: Additive versus diffusive coupling
The interaction between neural populations: Additive versus diffusive coupling
Abstract
Models of networks of populations of neurons commonly assume that the interactions between neural populations are via
...

