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We derive the Kullback-Leibler divergence for the normal-gamma distribution and show that it is identical to the Bayesian complexity penalty for the univariate general linear model with conjugate priors. Based on this finding, we provide…

Statistics Theory · Mathematics 2016-11-07 Joram Soch , Carsten Allefeld

We construct a class of exactly solvable generalized Kitaev spin-$1/2$ models in arbitrary dimensions, which is beyond the category of quantum compass models. The Jordan-Wigner transformation is employed to prove the exact solvability. An…

Strongly Correlated Electrons · Physics 2018-07-16 Jian-Jian Miao , Hui-Ke Jin , Fu-Chun Zhang , Yi Zhou

We introduce a new version of the KL-divergence for Gaussian distributions which is based on Wasserstein geometry and referred to as WKL-divergence. We show that this version is consistent with the geometry of the sample space ${\Bbb R}^n$.…

Statistics Theory · Mathematics 2026-05-29 Adwait Datar , Nihat Ay

We analyze the recently proposed mirror superposition experiment of Marshall, Simon, Penrose, and Bouwmeester, assuming that the mirror's dynamics contains a non-unitary term of the Lindblad type proportional to -[q,[q,\rho]], with q the…

Quantum Physics · Physics 2009-11-10 A. Bassi , E. Ippoliti , Stephen L. Adler

Kernel Regularized Least Squares (KRLS) is a popular method for flexibly estimating models that may have complex relationships between variables. However, its usefulness to many researchers is limited for two reasons. First, existing…

Machine Learning · Statistics 2023-09-12 Qing Chang , Max Goplerud

By the modified directed likelihood, higher order accurate confidence limits for a scalar parameter are obtained from the likelihood. They are conveniently described in terms of a confidence distribution, that is a sample dependent…

Statistics Theory · Mathematics 2016-07-19 Pierpaolo De Blasi , Tore Schweder

We perform a detailed investigation of the statistical properties of the projected distribution of galaxy clusters obtained in Cold Dark Matter (CDM) models with both Gaussian and skewed primordial density fluctuations. We use N-body…

Astrophysics · Physics 2015-06-24 S. Borgani , P. Coles , L. Moscardini , M. Plionis

This paper presents an algorithm for direct continuous-time (CT) identification of linear switched state-space (LSS) models. The key idea for direct CT identification is based on an integral architecture consisting of an LSS model followed…

Systems and Control · Electrical Eng. & Systems 2022-10-05 Manas Mejari , Dario Piga

The study of the scaling limit of two-dimensional models of statistical mechanics within the framework of integrable field theory is illustrated through the example of the RSOS models. Starting from the exact description of regime III in…

High Energy Physics - Theory · Physics 2009-10-31 G. Delfino

Sine-skewed circular distributions are identifiable and have easily-computable trigonometric moments and a simple random number generation algorithm, whereas they are known to have relatively low levels of asymmetry. This study proposes a…

Methodology · Statistics 2024-02-16 Yoichi Miyata , Takayuki Shiohama , Toshihiro Abe

In computational and applied statistics, it is of great interest to get fast and accurate calculation for the distributions of the quadratic forms of Gaussian random variables. This paper presents a novel approximation strategy that…

Methodology · Statistics 2023-12-29 Hong Zhang , Judong Shen , Zheyang Wu

A time-stepping L1 scheme for subdiffusion equation with a Riemann--Liouville time-fractional derivative is developed and analyzed. This is the first paper to show that the L1 scheme for the model problem under consideration is second-order…

Numerical Analysis · Mathematics 2019-09-17 Kassem Mustapha

Fully conditional specification (FCS) is a convenient and flexible multiple imputation approach. It specifies a sequence of simple regression models instead of a potential complex joint density for missing variables. However, FCS may not…

Computation · Statistics 2026-05-14 Mingyang Cai , Stef van Buuren , Gerko Vink

Kernel logistic regression (KLR) is a powerful classification method widely applied across diverse domains. In many real-world scenarios, indefinite kernels capture more domain-specific structural information than positive definite kernels.…

Machine Learning · Statistics 2025-10-31 Shaoxin Wang , Hanjing Yao

Conformal Predictors (CP) are wrappers around ML models, providing error guarantees under weak assumptions on the data distribution. They are suitable for a wide range of problems, from classification and regression to anomaly detection.…

Machine Learning · Computer Science 2021-10-06 Giovanni Cherubin , Konstantinos Chatzikokolakis , Martin Jaggi

We examine crossing probabilities and free energies for conformally invariant critical 2-D systems in rectangular geometries, derived via conformal field theory and Stochastic L\"owner Evolution methods. These quantities are shown to…

Mathematical Physics · Physics 2016-09-07 Peter Kleban , Don Zagier

The generalized Laplace (GL) distribution, which falls in the larger family of generalized hyperbolic distributions, provides a versatile model to deal with a variety of applications thanks to its shape parameters. The elliptically…

Methodology · Statistics 2025-04-15 Marco Geraci

We derive an exact, simple relation between the average number of clusters and the wrapping probabilities for two-dimensional percolation. The relation holds for periodic lattices of any size. It generalizes a classical result of Sykes and…

Statistical Mechanics · Physics 2017-01-04 Stephan Mertens , Robert M. Ziff

Many applications of generalised linear models (GLMs) can be improved by applying constraints that impose assumptions on the associations or improve consistency of the estimators. Yet, there are still barriers to the implementation and…

Methodology · Statistics 2026-02-19 Pierre Masselot , Devon Nenon , Jacopo Vanoli , Zaid Chalabi , Antonio Gasparrini

If the probability distribution model aims to approximate the hidden mother distribution, it is imperative to establish a useful criterion for the resemblance between the mother and the model distributions. This study proposes a criterion…

Statistics Theory · Mathematics 2025-11-13 Yo Sheena
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