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Consider the setting where there are B>1 candidate statistical models, and one is interested in model selection. Two common approaches to solve this problem are to select a single model or to combine the candidate models through model…

Methodology · Statistics 2021-04-22 Qingying Zong , Jonathan R. Bradley

The paper introduces a PDE model for the growth of a tree stem or a vine. The equations describe the elongation due to cell growth, and the response to gravity and to external obstacles. An additional term accounts for the tendency of a…

Optimization and Control · Mathematics 2020-11-10 Alberto Bressan , Michele Palladino , Wen Shen

In the presence of weak overall correlation, it may be useful to investigate if the correlation is significantly and substantially more pronounced over a subpopulation. Two different testing procedures are compared. Both are based on the…

Machine Learning · Statistics 2015-04-22 Stephen Bamattre , Rex Hu , Joseph S. Verducci

Copula modelling has in the past decade become a standard tool in many areas of applied statistics. However, a largely neglected aspect concerns the design of related experiments. Particularly the issue of whether the estimation of copula…

Methodology · Statistics 2014-06-12 Elisa Perrone , Werner G. Müller

Testing the validity of probabilistic models containing unmeasured (hidden) variables is shown to be a hard task. We show that the task of testing whether models are structurally incompatible with the data at hand, requires an exponential…

Artificial Intelligence · Computer Science 2013-02-28 Dan Geiger , Azaria Paz , Judea Pearl

When modeling the distribution of a multivariate continuous random vector using the so-called \emph{copula approach}, it is not uncommon to have ties in the coordinate samples of the available data because of rounding or lack of measurement…

Methodology · Statistics 2017-02-07 Ivan Kojadinovic

This paper addresses the problem of quantification and propagation of uncertainties associated with dependence modeling when data for characterizing probability models are limited. Practically, the system inputs are often assumed to be…

Computation · Statistics 2020-04-14 Jiaxin Zhang , Michael D. Shields

Standard penalized methods of variable selection and parameter estimation rely on the magnitude of coefficient estimates to decide which variables to include in the final model. However, coefficient estimates are unreliable when the design…

Methodology · Statistics 2018-02-13 Jonathan P Williams , Jan Hannig

The task of RNA design given a target structure aims to find a sequence that can fold into that structure. It is a computationally hard problem where some version(s) have been proven to be NP-hard. As a result, heuristic methods such as…

Biomolecules · Quantitative Biology 2024-12-13 Wei Yu Tang , Ning Dai , Tianshuo Zhou , David H. Mathews , Liang Huang

Truncated sum rules have been used to calculate the fundamental limits of the nonlinear susceptibilities; and, the results have been consistent with all measured molecules. However, given that finite-state models result in inconsistencies…

Optics · Physics 2016-09-08 Mark G. Kuzyk

Bayesian inference with nested sampling requires a likelihood-restricted prior sampling method, which draws samples from the prior distribution that exceed a likelihood threshold. For high-dimensional problems, Markov Chain Monte Carlo…

Computation · Statistics 2023-02-13 Johannes Buchner

A novel approach for dynamic modeling and forecasting of realized covariance matrices is proposed. Realized variances and realized correlation matrices are jointly estimated. The one-to-one relationship between a positive definite…

Methodology · Statistics 2019-02-18 Nicole Barthel , Claudia Czado , Yarema Okhrin

Both cluster randomized trials and quasi-experimental designs are used to evaluate the impact of health and social policies and interventions. Stepped-wedge cluster randomized trials randomize a staggered adoption approach, while recent…

Methodology · Statistics 2026-04-15 Haidong Lu , Gregg S. Gonsalves , Fan Li , Guanyu Tong , Lee Kennedy-Shaffer

We introduce the vine copula autoencoder (VCAE), a flexible generative model for high-dimensional distributions built in a straightforward three-step procedure. First, an autoencoder (AE) compresses the data into a lower dimensional…

Machine Learning · Statistics 2019-11-28 Natasa Tagasovska , Damien Ackerer , Thibault Vatter

We address the problem of model selection for Support Vector Machine (SVM) classification. For fixed functional form of the kernel, model selection amounts to tuning kernel parameters and the slack penalty coefficient $C$. We begin by…

Disordered Systems and Neural Networks · Physics 2007-05-23 Carl Gold , Peter Sollich

Woven shell structures are beneficial for applications requiring lightweight, damage resilience, and design tunability, such as in wearable devices, soft robotics, and aerospace systems. A fundamental component of woven structures is the…

Applied Physics · Physics 2025-12-02 Jaimie Krankel , Guowei Wayne Tu , Evgueni T. Filipov

Fitting models to data is an important part of the practice of science. Advances in machine learning have made it possible to fit more -- and more complex -- models, but have also exacerbated a problem: when multiple models fit the data…

Methodology · Statistics 2025-10-27 Alexandre René , André Longtin

The need for a method to construct multidimensional distribution function is increasing recently, in the era of huge multiwavelength surveys. We have proposed a systematic method to build a bivariate luminosity or mass function of galaxies…

Astrophysics of Galaxies · Physics 2020-09-02 Tsutomu T. Takeuchi , Kai T. Kono

The paper studies a PDE model for the growth of a tree stem or a vine, having the form of a differential inclusion with state constraints. The equations describe the elongation due to cell growth, and the response to gravity and to external…

Optimization and Control · Mathematics 2017-04-13 Bressan Alberto , Palladino Michele

This article presents factor copula approaches to model temporal dependency of non-Gaussian (continuous/discrete) longitudinal data. Factor copula models are canonical vine copulas which explain the underlying dependence structure of a…

Methodology · Statistics 2025-02-18 Subhajit Chattopadhyay
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