Results 61 to 70 of about 33,887 (293)

Modified One-Parameter Liu Estimator for the Linear Regression Model

Modelling and Simulation in Engineering, 2020
Motivated by the ridge regression (Hoerl and Kennard, 1970) and Liu (1993) estimators, this paper proposes a modified Liu estimator to solve the multicollinearity problem for the linear regression model.
Adewale F. Lukman, B. M. Golam Kibria, Kayode Ayinde, Segun L. Jegede   +3 more
doaj   +1 more source

Adaptive Monotone Shrinkage for Regression [PDF]

, 2015
We develop an adaptive monotone shrinkage estimator for regression models with the following characteristics: i) dense coefficients with small but important effects; ii) a priori ordering that indicates the probable predictive importance of the features.
Foster, Dean, Ma, Zhuang, Stine, Robert
core  

Log-concave Ridge Estimation

, 2020
We develop a density ridge search algorithm based on a novel density ridge definition. This definition is based on a conditional variance matrix and the mode in the lower dimensional subspace. It is compared to the subspace constraint mean shift algorithm, based on the gradient and Hessian of the underlying probability density function.
openaire   +2 more sources

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

Ridge Estimation with Nonlinear Transformations

, 2023
Ridge estimation is an important manifold learning technique. The goal of this paper is to examine the effects of nonlinear transformations on the ridge sets. The main result proves the inclusion relationship between ridges: $\cR(f\circ p)\subseteq \cR(p)$, provided that the transformation $f$ is strictly increasing and concave on the range of the ...
Zhai, Zheng, Chen, Hengchao, Yao, Zhigang   +2 more
openaire   +2 more sources

Peptide Sequencing With Single Acid Resolution Using a Sub‐Nanometer Diameter Pore

Advanced Functional Materials, EarlyView.
To sequence a single molecule of Aβ1−42–sodium dodecyl sulfate (SDS), the aggregate is forced through a sub‐nanopore 0.4 nm in diameter spanning a 4.0 nm thick membrane. The figure is a visual molecular dynamics (VMD) snapshot depicting the translocation of Aβ1−42–SDS through the pore; only the peptide, the SDS, the Na+ (yellow/green) and Cl− (cyan ...
Apurba Paul, Archith Rayabharam, Lisa Almonte, Eveline Rigo, Joshy Joseph, Ashutosh Kumar, Zhuxin Dong, Narayana Aluru, Gregory Timp   +8 more
wiley   +1 more source

On the Weighted Mixed Almost Unbiased Ridge Estimator in Stochastic Restricted Linear Regression

Journal of Applied Mathematics, 2013
We introduce the weighted mixed almost unbiased ridge estimator (WMAURE) based on the weighted mixed estimator (WME) (Trenkler and Toutenburg 1990) and the almost unbiased ridge estimator (AURE) (Akdeniz and Erol 2003) in linear regression model.
Chaolin Liu, Hu Yang, Jibo Wu
doaj   +1 more source

Joint Control of Radiated and Surface Waves via Space‐Time Coding Metasurfaces

Advanced Functional Materials, EarlyView.
A unified space‐time coding metasurface platform enables simultaneous control of radiated and surface‐confined waves across multiple harmonics. Demonstrated functionalities include multi‐frequency beam shaping; surface‐wave excitation, and hybrid multiplexing.
Zihao Dai, Yi Ning Zheng, Lei Zhang, Xiao Qing Chen, Giuseppe Castaldi, Tie Jun Cui, Vincenzo Galdi   +6 more
wiley   +1 more source

Penalized Regression with Correlation Based Penalty [PDF]

, 2006
A new regularization method for regression models is proposed. The criterion to be minimized contains a penalty term which explicitly links strength of penalization to the correlation between predictors.
Tutz, Gerhard, Ulbricht, Jan
core   +3 more sources

Interconnected Porous Hydrogels with Tunable Anisotropy Through Aqueous Emulsion Bioprinting

Advanced Functional Materials, EarlyView.
A 3D bioprintable microporous bioink is developed using an aqueous two‐phase system (ATPS) composed of extracellular matrix (ECM) mimetic biopolymers. The ATPS bioink enables the fabrication of interconnected porous architectures with up to 70% porosity, supporting long‐term cell viability and 3D cell alignment, enabling a simultaneous generation of ...
Hugo Edgar‐Vilar, Francisca P. Correia, Inês M. Freitas, Vítor M. Gaspar, João F. Mano   +4 more
wiley   +1 more source