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Neural demyelination and brain damage accumulated in white matter appear as hyperintense areas on T2-weighted MRI scans in the form of lesions. Modeling binary images at the population level, where each voxel represents the existence of a…

Methodology · Statistics 2023-05-29 Anna Menacher , Thomas E. Nichols , Chris Holmes , Habib Ganjgahi

In the management of most chronic conditions characterized by the lack of universally effective treatments, adaptive treatment strategies (ATSs) have been growing in popularity as they offer a more individualized approach, and sequential…

Methodology · Statistics 2021-08-03 Armando Turchetta , Erica E. M. Moodie , David A. Stephens , Sylvie D. Lambert

Static mechanical properties (e.g. elastic modulus) and fatigue properties of a material all have dispersions. Material inhomogeneity (it can be characterized well by the dispersion of elastic modulus) is the internal factor of dispersions…

Materials Science · Physics 2016-10-26 L Zhou , H M Qu

Bayesian estimation is increasingly popular for performing model based inference to support policymaking. These data are often collected from surveys under informative sampling designs where subject inclusion probabilities are designed to…

Methodology · Statistics 2018-07-13 Luis G. Leon-Novelo , Terrance D. Savitsky

Due to increased awareness of data protection and corresponding laws many data, especially involving sensitive personal information, are not publicly accessible. Accordingly, many data collecting agencies only release aggregated data, e.g.…

Methodology · Statistics 2022-04-12 Rajbir-Singh Nirwan , Nils Bertschinger

Decisions based upon pairwise comparisons of multiple treatments are naturally performed in terms of the mean survival of the selected study arms or functions thereof. However, synthesis of treatment comparisons is usually performed on…

Applications · Statistics 2025-12-11 Anastasios Apsemidis , Dimitris Mavridis , Nikolaos Demiris

Joint models for longitudinal and time-to-event data are widely used in many disciplines. Nonetheless, existing model comparison criteria do not indicate whether a model adequately fits the data or which components may be misspecified. We…

Methodology · Statistics 2026-01-27 Dimitris Rizopoulos , Jeremy M. G. Taylor , Isabella Kardys

Batteries are ubiquitous today, with applications ranging from smartphones, watches, and laptops to electric cars, drones, and electric aircraft. Lithium-ion batteries are widely used in these applications due to their high energy density,…

Computational Engineering, Finance, and Science · Computer Science 2026-03-03 Vikram C Patil

The heterogeneous microstructure in metallic components results in locally varying fatigue strength. Metal fatigue strongly depends on size and shape of non-metallic inclusions and pores, commonly referred to as "defects". Nodular cast iron…

Computational Engineering, Finance, and Science · Computer Science 2020-05-15 Christian Gebhardt , Torsten Trimborn , Felix Weber , Alexander Bezold , Christoph Broeckmann , Michael Herty

In this work, we study the use of logistic regression in manufacturing failures detection. As a data set for the analysis, we used the data from Kaggle competition Bosch Production Line Performance. We considered the use of machine…

Machine Learning · Computer Science 2016-12-31 B. Pavlyshenko

In recent times, products have become increasingly complex and highly reliable, so failures typically occur after long periods of operation under normal conditions and may arise from multiple causes. This paper employs simple step-stress…

Methodology · Statistics 2025-08-01 Rathin Das , Soumya Roy , Biswabrata Pradhan

Bayesian simulation-based inference (SBI) methods are used in statistical models where simulation is feasible but the likelihood is intractable. Standard SBI methods can perform poorly in cases of model misspecification, and there has been…

Methodology · Statistics 2025-04-15 Wang Yuyan , Michael Evans , David J. Nott

Accelerated life-testing (ALT) is a very useful technique for examining the reliability of highly reliable products. It allows testing the products at higher than usual stress conditions to induce failures more quickly and economically than…

Statistics Theory · Mathematics 2020-05-15 Aida Calviño

Throughout the different phases of a drug development program, randomized trials are used to establish the tolerability, safety, and efficacy of a candidate drug. At each stage one aims to optimize the design of future studies by…

Applications · Statistics 2021-02-08 Sebastian Weber , Andrew Gelman , Daniel Lee , Michael Betancourt , Aki Vehtari , Amy Racine

Metallicity can be measured by analyzing the spectra in the X-ray region and comparing the flux in spectral lines to the flux in the underlying Bremsstrahlung continuum. In this paper we propose new Bayesian methods which directly model the…

Astrophysics · Physics 2007-05-23 Epaminondas Sourlas , David van Dyk , Vinay Kashyap , Jeremy Drake , Deron Pease

The goal of this paper is to compare several widely used Bayesian model selection methods in practical model selection problems, highlight their differences and give recommendations about the preferred approaches. We focus on the variable…

Methodology · Statistics 2017-12-18 Juho Piironen , Aki Vehtari

Reliable uncertainty quantification remains a central challenge in predictive modeling. While Bayesian methods are theoretically appealing, their predictive intervals can exhibit poor frequentist calibration, particularly with small sample…

Methodology · Statistics 2025-08-05 Graham Gibson

We study objective Bayesian inference for linear regression models with residual errors distributed according to the class of two-piece scale mixtures of normal distributions. These models allow for capturing departures from the usual…

Applications · Statistics 2016-05-09 F. J. Rubio , K. Yu

Accurate prediction of turbine blade fatigue life is essential for ensuring the safety and reliability of aircraft engines. A significant challenge in this domain is uncovering the intrinsic relationship between mechanical properties and…

Machine Learning · Computer Science 2024-12-06 Pei Li , Joo-Ho Choi , Dingyang Zhang , Shuyou Zhang , Yiming Zhang

Stochastic kinetic models are often used to describe complex biological processes. Typically these models are analytically intractable and have unknown parameters which need to be estimated from observed data. Ideally we would have…

Computation · Statistics 2018-03-13 Richard J. Boys , Holly F. Ainsworth , Colin S. Gillespie