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Many psychological theories can be operationalized as linear inequality constraints on the parameters of multinomial distributions (e.g., discrete choice analysis). These constraints can be described in two equivalent ways: Either as the…

Computation · Statistics 2019-04-23 Daniel W. Heck , Clintin P. Davis-Stober

Monte-Carlo techniques are standard numerical tools for exploring non-Gaussian and multivariate likelihoods. Many variants of the original Metropolis-Hastings algorithm have been proposed to increase the sampling efficiency. Motivated by…

Cosmology and Nongalactic Astrophysics · Physics 2024-10-31 Maximilian Philipp Herzog , Heinrich von Campe , Rebecca Maria Kuntz , Lennart Röver , Björn Malte Schäfer

We study the maximum entropy (MaxEnt) approach for analytical continuation of spectral data from imaginary times to real frequencies. The total error is divided in a statistical error, due to the noise in the input data, and a systematic…

Data Analysis, Statistics and Probability · Physics 2010-11-16 O. Gunnarsson , M. W. Haverkort , G. Sangiovanni

In this note we consider the finite-dimensional parameter estimation problem associated to inverse problems. In such scenarios, one seeks to maximize the marginal likelihood associated to a Bayesian model. This latter model is connected to…

Numerical Analysis · Mathematics 2025-04-10 Ajay Jasra , Abylay Zhumekenov

In the works on Statistical Mechanics and Statistical Physics, when deriving the distribution of particles of ideal gases, one uses the method of Lagrange multipliers in a formal way. In this paper we treat rigorously this problem for…

Mathematical Physics · Physics 2016-01-12 Constantin Zalinescu

The canonical ensemble describes an open system in equilibrium with a heat bath of fixed temperature. The probability distribution of such a system, the Boltzmann distribution, is derived from the uniform probability distribution of the…

Statistical Mechanics · Physics 2015-06-05 Julian Lee

Statistical mechanics is widely applied to solve hard optimization problem, the optimal strategy related to ground state energy that depends on low temperature. Common thermodynamic process is expected to approach the ground state energy if…

Computational Physics · Physics 2020-08-19 Yusupjan Habibulla

In this article, the solution of a statistical inverse problem $M = AU+\mathcal{E}$ by the Bayesian approach is studied where $U$ is a function on the unit circle $\mathbb{T}$, i.e., a periodic signal. The mapping $A$ is a smoothing linear…

Statistics Theory · Mathematics 2009-07-31 Tapio Helin

Bayesian statistical inverse problems are often solved with Markov chain Monte Carlo (MCMC)-type schemes. When the problems are governed by large-scale discrete nonlinear partial differential equations (PDEs), they are computationally…

Numerical Analysis · Mathematics 2019-09-06 Howard C. Elman , Akwum Onwunta

A multicanonical formalism is applied to the problem of statistical equilibrium in a complex system with a hierarchy of dynamical structures. At the small scales the system is in quasi-equilibrium and follows a Maxwell-Boltzmann…

Statistical Mechanics · Physics 2012-08-29 G. L. Vasconcelos , D. S. P. Salazar

This work deals with parallel optimization of expensive objective functions which are modeled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit…

Machine Learning · Statistics 2019-09-04 Sébastien Marmin , Clément Chevalier , David Ginsbourger

We address the problem of minimizing a quadratic function subject to linear constraints over binary variables. We introduce the exact solution method called EXPEDIS where the constrained problem is transformed into a max-cut instance, and…

Optimization and Control · Mathematics 2022-04-12 Nicolo Gusmeroli , Angelika Wiegele

Bayesian methods suffer from the problem of how to specify prior beliefs. One interesting idea is to consider worst-case priors. This requires solving a stochastic zero-sum game. In this paper, we extend well-known results from bandit…

Machine Learning · Computer Science 2014-12-11 Emmanouil G. Androulakis , Christos Dimitrakakis

The problem of efficiently computing the betweenness centrality of nodes has been researched extensively. To date, the best known exact and centralized algorithm for this task is an algorithm proposed in 2001 by Brandes. The contribution of…

Data Structures and Algorithms · Computer Science 2015-06-05 Dora Erdos , Vatche Ishakian , Azer Bestavros , Evimaria Terzi

In most data-scientific approaches, the principle of Maximum Entropy (MaxEnt) is used to a posteriori justify some parametric model which has been already chosen based on experience, prior knowledge or computational simplicity. In a…

Methodology · Statistics 2022-06-29 Orestis Loukas , Ho Ryun Chung

In Clearing Up Mysteries -- The Original Goal (Maximum Entropy and Bayesian Methods: Cambridge, England, 1988 Springer, pp. 1-27) Jaynes derived Fick's Law for a dilute binary solution from Bayes' Theorem by considering, probabilistically,…

Statistical Mechanics · Physics 2024-07-02 Peter E. Price

The superstatistics approach recently introduced by Beck [C. Beck and E.G.D. Cohen, Physica A 322, 267 (2003)] is a formalism that aims to deal in a unifying way with a large variety of complex nonequilibrium systems, for which…

Statistical Mechanics · Physics 2007-05-23 Fabio Sattin

We derive asymptotic formulas for the number of integer partitions with given sums of $j$th powers of the parts for $j$ belonging to a finite, non-empty set $J \subset \mathbb N$. The method we use is based on the `principle of maximum…

Combinatorics · Mathematics 2021-01-01 Gweneth McKinley , Marcus Michelen , Will Perkins

The universal validity of the second law of thermodynamics is widely attributed to a finely tuned initial condition of the universe. This creates a problem: why is the universe atypical? We suggest that the problem is an artefact created by…

General Relativity and Quantum Cosmology · Physics 2015-07-27 Julian Barbour , Tim Koslowski , Flavio Mercati

The maximum entropy principle from statistical mechanics states that a closed system attains an equilibrium distribution that maximizes its entropy. We first show that for graphs with fixed number of edges one can define a stochastic edge…

Disordered Systems and Neural Networks · Physics 2007-05-23 Jesse S. A. Bridgewater , P. Oscar Boykin , Vwani P. Roychowdhury