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Related papers: Parameter estimation for Gibbs distributions

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The distribution of the ratios of nearest neighbor level spacings has become a popular indicator of spectral fluctuations in complex quantum systems like interacting many-body localized and thermalization phases, quantum chaotic systems,…

Quantum Physics · Physics 2021-08-12 S. Harshini Tekur , Udaysinh T. Bhosale , M. S. Santhanam

We study the problem of robustly estimating the mean or location parameter without moment assumptions. We show that for a large class of symmetric distributions, the same error as in the Gaussian setting can be achieved efficiently. The…

Data Structures and Algorithms · Computer Science 2023-11-09 Gleb Novikov , David Steurer , Stefan Tiegel

In this article, a generalized version of Negative binomial-beta exponential distribution with five parameters have been introduced. Some interesting submodels have been derived from it. A comprehensive mathematical treatment of proposed…

Statistics Theory · Mathematics 2019-05-31 Anwar Hassan , Ishfaq Shah Ahmad , Peer Bilal Ahmad

We present quantum algorithms for solving two problems regarding stochastic processes. The first algorithm prepares the thermal Gibbs state of a quantum system and runs in time almost linear in $\sqrt{N \beta/{\cal Z}}$ and polynomial in…

Quantum Physics · Physics 2017-01-11 Anirban Narayan Chowdhury , Rolando D. Somma

We introduce in this paper a new generalization of the flexible Weibull distribution with four parameters. This model based on the Beta generalized (BG) distribution, Eugene et al. \cite{Eugeneetal2002}, they first using the BG distribution…

Statistics Theory · Mathematics 2017-03-20 Beih S. El-Desouky , Abdelfattah Mustafa , Shamsan AL-Garash

A statistical model M is a family of probability distributions, characterised by a set of continuous parameters known as the parameter space. This possesses natural geometrical properties induced by the embedding of the family of…

General Relativity and Quantum Cosmology · Physics 2009-10-30 Dorje C. Brody , Lane P. Hughston

We study the asymptotic properties of parameter estimation and predictive inference under the exchangeable Gibbs partition, characterized by a discount parameter $\alpha\in(0,1)$ and a triangular array $v_{n,k}$ satisfying a backward…

Statistics Theory · Mathematics 2026-04-07 Takuya Koriyama

Sampling from Gibbs distributions and computing their log-partition function are fundamental tasks in statistics, machine learning, and statistical physics. While efficient algorithms are known for log-concave densities, the worst-case…

Machine Learning · Statistics 2026-04-24 David Holzmüller , Francis Bach

The beta distribution is a basic distribution serving several purposes. It is used to model data, and also, as a more flexible version of the uniform distribution, it serves as a prior distribution for a binomial probability. The bivariate…

Methodology · Statistics 2014-09-17 Ingram Olkin , Thomas A. Trikalinos

The norm of an integer partition is defined as the product of its parts. This statistic was recently introduced by Schneider in connection to partition zeta functions. In this note, we use the method of moments to study the distribution of…

Combinatorics · Mathematics 2023-08-02 Walter Bridges , William Craig

Partition function of beta-gamma systems on the orbifolds C^2/Z_N and C^3/Z_M x Z_N are obtained as the invariant part of that on the respective affine spaces, by lifting the geometric action of the orbifold group to the fields.…

High Energy Physics - Theory · Physics 2015-06-17 Chandrasekhar Bhamidipati , Koushik Ray

The Gibbs partition function is an important quantity in describing statistical properties of a system in thermodynamic equilibrium. There are several proposals to calculate the partition functions on near-team quantum computers. However,…

This paper presents different recursive formulas for computing the marginals and the normalizing constant of a Gibbs distribution $\pi$: The common thread is the use of the underlying Markov properties of such processes. The procedures are…

Probability · Mathematics 2025-11-07 Cécile Hardouin , Xavier Guyon

The beta distribution is a two-parameter family of probability distributions whose distribution function is the (regularised) incomplete beta function. In this paper, the inverse incomplete beta function is studied analytically as…

Classical Analysis and ODEs · Mathematics 2017-10-27 Dimitris Askitis

We present a near-optimal reduction from approximately counting the cardinality of a discrete set to approximately sampling elements of the set. An important application of our work is to approximating the partition function $Z$ of a…

Data Structures and Algorithms · Computer Science 2007-05-23 Daniel Stefankovic , Santosh Vempala , Eric Vigoda

The need to condition distributional properties such as expectation, variance, and entropy arises in algorithmic fairness, model simplification, robustness and many other areas. At face value however, distributional properties are not…

Programming Languages · Computer Science 2019-03-27 Zenna Tavares , Xin Zhang , Edgar Minaysan , Javier Burroni , Rajesh Ranganath , Armando Solar Lezama

The most well known probability distribution of probabilities is the Beta distribution. If we have observed $r$ `successes', each having a probability $\theta$, and $n-r$ `failures', each having a probability $1-\theta$. In this paper we…

Methodology · Statistics 2015-03-04 H. R. N. van Erp , R. O. Linger , P. H. A. J. M. van Gelder

The aim of this article is to determine a new six-parameter Beta Weibull distribution and its various associated functions, namely the cumulative distribution, survival, probability density and hazard functions. Next, we determine the…

Statistics Theory · Mathematics 2026-04-07 Didier Alain Njamen Njomen , Fidel Djongreba Ndikwa

We propose a generalisation of Gibbs' statistical mechanics into the domain of non-negligible phase space correlations. Derived are the probability distribution and entropy as a generalised ensemble average, replacing…

Statistical Mechanics · Physics 2014-09-10 R. A. Treumann , W. Baumjohann

Some scenarios require the computation of a predictive distribution of a new value evaluated on an objective function conditioned on previous observations. We are interested on using a model that makes valid assumptions on the objective…

Machine Learning · Computer Science 2021-01-21 Lucia Asencio-Martín , Eduardo C. Garrido-Merchán
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