Results 101 to 110 of about 1,310,642 (283)

EMPIRICAL LIKELIHOOD ESTIMATORS OF THE LINEAR SIMULTANEOUS EQUATIONS MODEL [PDF]

Information theoretic estimators are specified for a system of linear simultaneous equations, including maximum empirical likelihood, maximum empirical exponential likelihood, and maximum log Euclidean likelihood.
Judge, George G., Marsh, Thomas L., Mittelhammer, Ronald C.   +2 more
core   +1 more source

Maximum Augmented Empirical Likelihood Estimation of Categorical Marginal Models for Large Sparse Contingency Tables. [PDF]

Psychometrika, 2023
van der Ark LA, Bergsma WP, Koopman L.
europepmc   +1 more source

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

Advanced 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, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Empirical Inferences Under Bayesian Framework to Identify Cellwise Outliers

Stats
Outliers are typically identified using frequentist methods. The data are classified as “outliers” or “not outliers” based on a test statistic that measures the magnitude of the difference between a value and the majority part of the data.
Luca Sartore, Lu Chen, Valbona Bejleri
doaj   +1 more source

Variable selection in generalized random coefficient autoregressive models

Journal of Inequalities and Applications, 2018
In this paper, we consider the variable selection problem of the generalized random coefficient autoregressive model (GRCA). Instead of parametric likelihood, we use non-parametric empirical likelihood in the information theoretic approach. We propose an
Zhiwen Zhao, Yangping Liu, Cuixin Peng
doaj   +1 more source

Empirical Likelihood for a First-Order Generalized Random Coefficient Integer-Valued Autoregressive Process. [PDF]

J Syst Sci Complex, 2023
Cheng J, Wang X, Wang D.
europepmc   +1 more source

Innovative Processing of Compacted Waste Aluminum Alloy Powders via Controlled Remelting and Solidification

Advanced Engineering Materials, EarlyView.
This study demonstrates an efficient recycling route for out‐of‐spec AlSi10Mg atomized powders through compaction and arc remelting followed by suction casting. By correlating compaction load, cooling rate, and resulting microstructure, we show that intermediate pressures (50–80 kN) and rapid cooling refine dendrites, reduce porosity, and enhance ...
Mila Christy de Oliveira, Marcella Gaute Cavalcante Xavier, Abdoul‐Aziz Bogno, Piter Gargarella, José Eduardo Spinelli   +4 more
wiley   +1 more source

Empirical likelihood confidence interval for sensitivity to the early disease stage. [PDF]

Pharm Stat, 2022
Rahman H, Zhao Y, Alzheimer's Disease Neuroimaging Initiative.   +2 more
europepmc   +1 more source

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

Advanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source

Evaluation of spatial Bayesian Empirical Likelihood models in analysis of small area data. [PDF]

PLoS One, 2022
Jahan F, Kennedy DW, Duncan EW, Mengersen KL.   +3 more
europepmc   +1 more source