Results 81 to 90 of about 2,103,105 (303)

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

open access: yesAdvanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt   +8 more
wiley   +1 more source

Bayesian Sperm Competition Estimates

open access: yesGenetics, 2003
Abstract We introduce a Bayesian method for estimating parameters for a model of multiple mating and sperm displacement from genotype counts of brood-structured data. The model is initially targeted for Drosophila melanogaster, but is easily adapted to other organisms. The method is appropriate for use with field studies where the number
Beatrix, Jones, Andrew G, Clark
openaire   +2 more sources

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

open access: yesAdvanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice   +2 more
wiley   +1 more source

A Bayesian copula model for stochastic claims reserving [PDF]

open access: yes
We present a full Bayesian model for assessing the reserve requirement of multiline Non-Life insurance companies. Bayesian models for claims reserving allow to account for expert knowledge in the evaluation of Outstanding Loss Liabilities, allowing the ...
Luca Regis
core   +2 more sources

Bayesian Estimation of Unknown Heteroscedastic Variances [PDF]

open access: yes
We propose a Bayesian procedure to estimate possibly heteroscedastic variances of the regression error term, without assuming any structure on them. What we propose in this paper, may be construed as a Conditional Bayesian procedure that is conditioned ...
Tsunemasa Shiba, Hiroaki Chigira
core  

Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy

open access: yesAdvanced Engineering Materials, EarlyView.
Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang   +6 more
wiley   +1 more source

Statistical inference for nonignorable missing-data problems: a selective review

open access: yesStatistical Theory and Related Fields, 2018
Nonignorable missing data are frequently encountered in various settings, such as economics, sociology and biomedicine. We review statistical inference for nonignorable missing-data problems, including estimation, influence analysis and model selection ...
Niansheng Tang, Yuanyuan Ju
doaj   +1 more source

Approximate inference of the bandwidth in multivariate kernel density estimation [PDF]

open access: yes, 2011
Kernel density estimation is a popular and widely used non-parametric method for data-driven density estimation. Its appeal lies in its simplicity and ease of implementation, as well as its strong asymptotic results regarding its convergence to the true ...
Sanguinetti, G.   +3 more
core   +1 more source

Investigation of Resonance Characteristics of More Than 10 000 Metal‐Coated Silicon MEMS Cantilevers Using Machine Learning

open access: yesAdvanced Engineering Materials, EarlyView.
More than 10 000 metal‐coated silicon MEMS cantilevers are fabricated and characterized to build a large‐scale experimental dataset spanning multiple vibrational modes. Machine learning algorithms are benchmarked to predict resonance frequency and quality factor, with ensemble based models achieving accuracy approaching experimental uncertainty.
Sina Zare Pakzad   +8 more
wiley   +1 more source

Selection effect of learning rate parameter on estimators of k exponential populations under the joint hybrid censoring

open access: yesHeliyon
A Bayesian method based on the learning rate parameter η is called a generalized Bayesian method. In this study, joint hybrid censored type I and type II samples from k exponential populations were examined to determine the influence of the parameter η ...
Yahia Abdel-Aty   +2 more
doaj   +1 more source

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