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Nested error regression models are useful tools for analysis of grouped data, especially in the case of small area estimation. This paper suggests a nested error regression model using uncertain random effects in which the random effect in…

Methodology · Statistics 2017-02-28 Shonosuke Sugasawa , Tatsuya Kubokawa

We derive large-sample and other limiting distributions of the ``frequency of frequencies'' vector, ${\bf M_n}$, together with the number of species, $K_n$, in a Poisson-Dirichlet or generalised Poisson-Dirichlet gene or species sampling…

Statistics Theory · Mathematics 2023-09-06 Ross Maller , Soudabeh Shemehsavar

The aim of this paper is to give fine asymptotics for random variables with moments of Gamma type. Among the examples we consider are random determinants of Laguerre and Jacobi beta ensembles with varying dimensions (the number of observed…

Probability · Mathematics 2017-10-19 Peter Eichelsbacher , Lukas Knichel

The main aim of this article is to characterize and investigate the three parameter exponentiated exponential Poisson probability distribution ${\rm EEP}(\alpha, \beta, \lambda)$ by giving explicit closed form expressions for its…

Statistics Theory · Mathematics 2014-02-04 Tibor K Pogány

It is known that the M\"obius function in number theory is higher order oscillating. In this paper we show that there is another kind of higher order oscillating sequences in the form $(e^{2\pi i \alpha \beta^{n}g(\beta)})_{n\in \N}$, for a…

Dynamical Systems · Mathematics 2020-06-02 Shigeki Akiyama , Yunping Jiang

It has been observed that an interesting class of non-Gaussian stationary processes is obtained when in the harmonics of a signal with random amplitudes and phases, frequencies can also vary randomly. In the resulting models, the…

Probability · Mathematics 2019-11-19 Anastassia Baxevani , Krzysztof Podgórski

We compute analytically, for large N, the probability distribution of the number of positive eigenvalues (the index N_{+}) of a random NxN matrix belonging to Gaussian orthogonal (\beta=1), unitary (\beta=2) or symplectic (\beta=4)…

Statistical Mechanics · Physics 2015-05-14 Satya N. Majumdar , Celine Nadal , Antonello Scardicchio , Pierpaolo Vivo

When data analysts train a classifier and check if its accuracy is significantly different from chance, they are implicitly performing a two-sample test. We investigate the statistical properties of this flexible approach in the…

Machine Learning · Computer Science 2020-02-18 Ilmun Kim , Aaditya Ramdas , Aarti Singh , Larry Wasserman

Gibbs partition models are the largest class of infinite exchangeable partitions of the positive integers generalizing the product form of the probability function of the two-parameter Poisson-Dirichlet family. Recently those models have…

Probability · Mathematics 2013-12-23 Annalisa Cerquetti

This paper is concerned with the study of the random variable $K_n$ denoting the number of distinct elements in a random sample $(X_1, \dots, X_n)$ of exchangeable random variables driven by the two parameter Poisson-Dirichlet distribution,…

Probability · Mathematics 2020-09-22 Emanuele Dolera , Stefano Favaro

Consider a discrete locally finite subset $\Gamma$ of $R^d$ and the complete graph $(\Gamma,E)$, with vertices $\Gamma$ and edges $E$. We consider Gibbs measures on the set of sub-graphs with vertices $\Gamma$ and edges $E'\subset E$. The…

Probability · Mathematics 2010-09-17 Pablo A. Ferrari , Eugene A. Pechersky , Valentin V. Sisko , Anatoly A. Yambartsev

The problem of estimating location (scale) parameters $\theta_1$ and $\theta_2$ of two distributions when the ordering between them is known apriori (say, $\theta_1\leq \theta_2$) has been extensively studied in the literature. Many of…

Statistics Theory · Mathematics 2022-07-05 Naresh Garg , Neeraj Misra

In this paper, we consider the problem of partitioning a small data sample of size $n$ drawn from a mixture of $2$ sub-gaussian distributions. Our work is motivated by the application of clustering individuals according to their population…

Statistics Theory · Mathematics 2023-01-05 Shuheng Zhou

We study the statistical properties of the generation of random graphs according the configuration model, where one assigns randomly degrees to nodes. This model is often used, e.g., for the scale-free degree distribution ~d^gamma. For the…

Disordered Systems and Neural Networks · Physics 2015-05-28 Hendrike Klein-Hennig , Alexander K. Hartmann

A class of discrete distributions can be derived from stationary renewal processes. They have the useful property that the mean is a simple function of the model parameters. Thus regressions of the distribution mean on covariates can be…

Methodology · Statistics 2018-03-01 Rose Baker

We consider a version of D. Price's model for the growth of a bibliographic network, where in each iteration a constant number of citations is randomly allocated according to a weighted combination of accidental (uniformly distributed) and…

Physics and Society · Physics 2022-08-31 Grzegorz Siudem , Przemysław Nowak , Marek Gagolewski

We compute the full order statistics of a one-dimensional gas of fermions in a harmonic trap at zero temperature, including its large deviation tails. The problem amounts to computing the probability distribution of the $k$th smallest…

Statistical Mechanics · Physics 2014-11-05 Isaac Pérez Castillo

We derive explicit Bayesian nonparametric analysis for a species sampling model with finitely many types of Gibbs form of type $\alpha= -1$ recently introduced in Gnedin (2009). Our results complement existing analysis under Gibbs priors of…

Probability · Mathematics 2010-01-05 Annalisa Cerquetti

Four new probability models are derived which generalize the common univariate continuous distributions. Classical distributional measures are derived from Hoel, et al., Introduction to Probability Theory, 1971. Measures include probability…

General Mathematics · Mathematics 2014-05-09 Francis J. O'Brien

The generalized negative binomial distribution (GNB) is a new flexible family of discrete distributions that are mixed Poisson laws with the mixing generalized gamma (GG) distributions. This family of discrete distributions is very wide and…

Methodology · Statistics 2018-09-18 Andrey K. Gorshenin , Victor Yu. Korolev
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