Results 131 to 140 of about 25,682 (291)

Novel Data-Driven Shrinkage Ridge Parameters for Handling Multicollinearity in Regression Models with Environmental and Chemical Data Applications

Axioms
Multicollinearity among predictor variables is a common challenge in modeling chemical and environmental datasets in physical sciences, often leading to collinearity issues and unreliable parameter estimates when fitting regression models.
Muteb Faraj Alharthi
doaj   +1 more source

Hierarchical shrinkage priors for dynamic regressions with many predictors [PDF]

This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarchical Normal-Gamma priors. Various popular penalized least squares estimators for shrinkage and selection in regression models can be recovered using this ...
Korobilis, Dimitris
core   +1 more source

Mechanical Properties of Architected Polymer Lattice Materials: A Comparative Study of Additive Manufacturing and CAD Using FEM and µ‐CT

Advanced Functional Materials, EarlyView.
This study examines how pore shape and manufacturing‐induced deviations affect the mechanical properties of 3D‐printed lattice materials with constant porosity. Combining µ‐CT analysis, FEM, and compression testing, the authors show that structural imperfections reduce stiffness and strength, while bulk material inhomogeneities probably enhance ...
Oliver Walker, Thierry Roland, Damien Favier, Antoine Egele, Michael Heymann, Cosima Stubenrauch   +5 more
wiley   +1 more source

"Simultaneous estimation of normal precision matrices" [PDF]

This paper treats the problem of simultaneously estimating the precision matrices in multivariate normal distributions. A condition for improvement on the unbiased estimators of the precision matrices is derived under a quadratic loss function.
Hisayuki Tsukuma, Tatsuya Kubokawa
core  

Reevaluating the Activity of ZIF‐8 Based FeNCs for Electrochemical Ammonia Production

Advanced Functional Materials, EarlyView.
Though receiving much attention, the field of electrochemical nitrogen reduction reaction (eNRR) to ammonia is marked by doubts about whether this reaction is possible in aqueous media. This work sheds light on this question for iron single‐atom on N‐doped carbon (FeNC) catalysts—a class of well‐known catalysts that is also worth testing for the sister
Caroline Schneider, S. Esmael Balaghi, Niklas Ortlieb, Patrick Elsaesser, Sima Heidari, Christopher S. Allen, Anna Fischer   +6 more
wiley   +1 more source

Cool Kitchen: Processing Starch and Eggshell Powder into Sustainable Coatings for Passive Daytime Cooling

Advanced Functional Materials, EarlyView.
A food‐grade cooling composite made from starch and recycled eggshell powder offers a scalable, ultra‐low‐cost solution for passive daytime radiative cooling. Easily prepared using basic kitchen tools, this material empowers communities, even in areas with limited infrastructure, to stay cooler during worsening summer heat waves.
Qimeng Song, Evelyn Kubacki, Alexander Berger, Markus Retsch   +3 more
wiley   +1 more source

MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance

Advanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Optimal Shrinkage Estimations for the Parameters of Exponential Distribution Based on Record Values

Revista Colombiana de Estadística
This paper studies shrinkage estimation after the preliminary test for the parameters of exponential distribution based on record values. The optimal value of shrinkage coefficients is also obtained based on the minimax regret criterion.
HOJATOLLAH ZAKERZADEH, ALI AKBAR JAFARI, MAHDIEH KARIMI   +2 more
doaj  

Optimal Linear Shrinkage Estimator for Large Dimensional Precision Matrix

, 2014
In this work we construct an optimal shrinkage estimator for the precision matrix in high dimensions. We consider the general asymptotics when the number of variables $p\rightarrow\infty$ and the sample size $n\rightarrow\infty$ so that $p/n\rightarrow c\
Bodnar, Taras, Gupta, Arjun K., Parolya, Nestor   +2 more
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