A random clustering distribution is useful for modeling count data. The present article derives a new distribution of this type from the Lagrangian Poisson distribution, based on the result that any infinitely divisible distribution over nonnegative integers produces a random clustering distribution through conditioning and a limiting argument that is equivalent to the law of small numbers. The resulting distribution is shown to be tractable. Its application is also presented.本文フィルはリンク先を参照のこ
In 2007, we introduced a general model of sparse random graphs with (conditional) independence betwe...
金沢大学人間社会研究域経済学経営学系The present article describes a Conditional Inverse Gaussian-Poisson (CIGP) distri...
We develop a simple and unified approach to investigate several aspects of the cluster statistics of...
<p>Motivated by the fundamental problem of modeling the frequency of frequencies (FoF) distribution,...
The present article investigates a class of random partitioning distributions of a positive integer....
Many popular random partition models, such as the Chinese restaurant process and its two-parameter e...
In the present work we present, for the first time ever, the exact configuration integral entering t...
The paper introduces the concept of a cluster structure to define a joint distribution of the sample...
This paper presents a new derivation of the Generalized Poisson distribution. The derivation is base...
AbstractGiven a random graph, we investigate the occurrence of subgraphs especially rich in edges. S...
Motivated by the fundamental problem of measuring species diversity, this paper introduces the conce...
Divisible statistics have been widely used in many areas of statistical analysis. For example, Pears...
Abstract—The goal of data clustering is to partition data points into groups to optimize a given obj...
The goal of data clustering is to partition data points into groups to optimize a given objective fu...
The goal of this paper is to discuss statistical aspects of clustering in a framework where the data...
In 2007, we introduced a general model of sparse random graphs with (conditional) independence betwe...
金沢大学人間社会研究域経済学経営学系The present article describes a Conditional Inverse Gaussian-Poisson (CIGP) distri...
We develop a simple and unified approach to investigate several aspects of the cluster statistics of...
<p>Motivated by the fundamental problem of modeling the frequency of frequencies (FoF) distribution,...
The present article investigates a class of random partitioning distributions of a positive integer....
Many popular random partition models, such as the Chinese restaurant process and its two-parameter e...
In the present work we present, for the first time ever, the exact configuration integral entering t...
The paper introduces the concept of a cluster structure to define a joint distribution of the sample...
This paper presents a new derivation of the Generalized Poisson distribution. The derivation is base...
AbstractGiven a random graph, we investigate the occurrence of subgraphs especially rich in edges. S...
Motivated by the fundamental problem of measuring species diversity, this paper introduces the conce...
Divisible statistics have been widely used in many areas of statistical analysis. For example, Pears...
Abstract—The goal of data clustering is to partition data points into groups to optimize a given obj...
The goal of data clustering is to partition data points into groups to optimize a given objective fu...
The goal of this paper is to discuss statistical aspects of clustering in a framework where the data...
In 2007, we introduced a general model of sparse random graphs with (conditional) independence betwe...
金沢大学人間社会研究域経済学経営学系The present article describes a Conditional Inverse Gaussian-Poisson (CIGP) distri...
We develop a simple and unified approach to investigate several aspects of the cluster statistics of...