Results 111 to 120 of about 24,864 (292)
Advanced Science, EarlyView.A bioinspired piezoelectric sensor mimicking Pacinian corpuscles is developed to enable ultrasensitive and linear pressure sensing. A multilayer grooved architecture converts normal pressure into in‐plane strain, delivering high sensitivity, wide linear range, and efficient energy harvesting, enabling high‐fidelity wrist pulse monitoring and ...
Qi Yang +8 more
wiley +1 more source
Comparison of Some Estimators under the Pitman’s Closeness Criterion in Linear Regression Model
Journal of Applied Mathematics, 2014 Batah et al. (2009) combined the unbiased ridge estimator and principal components regression estimator and introduced the modified r-k class estimator.
Jibo Wu
doaj +1 more source
Beyond the Ban—Shedding Light on Smallholders' Price Vulnerability in Indonesia's Palm Oil Industry
Applied Economic Perspectives and Policy, EarlyView.ABSTRACT The Indonesian government imposed a palm oil export ban in April 2022 to address rising cooking oil prices. This study explores oil palm smallholders' vulnerability to the policy using descriptive statistics, Lasso, and post‐Lasso OLS regressions.
Charlotte‐Elena Reich +3 more
wiley +1 more source
The performance of some new estimated ridge parameter regression model [PDF]
مجلة جامعة الانبار للعلوم الصرفةIn the presence of high correlation between the independent variables in the linear regression model, which is known as the multicollinearity problem, the ordinary least squares estimator produces large variations in the sample. To overcome this problem,
Fatima ALfahdawe, Mustafa Alheety
doaj +1 more source
Nonlinear Forecasting with Many Predictors using Kernel Ridge Regression [PDF]
, 2011 This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable.
Dijk, D.J.C. (Dick) van +3 more
core
Advanced Intelligent Discovery, EarlyView.Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang +5 more
wiley +1 more source
Computational Journal of Mathematical and Statistical SciencesThe multicollinearity problem occurrence of the explanatory variables affects the least-squares (LS) estimator seriously in the regression models. The multicollinearity adverse effects on the LS estimation are also investigated by many authors.
Mohamed Reda Abonazel
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.This work establishes a correlation between solvent properties and the charge transport performance of solution‐processed organic thin films through interpretable machine learning. Strong dispersion interactions (δD), moderate hydrogen bonding (δH), closely matching and compatible with the solute (quadruple thiophene), and a small molar volume (MolVol)
Tianhao Tan, Lian Duan, Dong Wang
wiley +1 more source
Affine Invariant Covariance Estimation for Heavy-Tailed Distributions [PDF]
, 2019 In this work we provide an estimator for the covariance matrix of a heavy-tailed multivariate distributionWe prove that the proposed estimator $\widehat{\mathbf{S}}$ admits an \textit{affine-invariant} bound of the form \[(1-\varepsilon) \mathbf{S ...
Ostrovskii, Dmitrii, Rudi, Alessandro
core +3 more sources
The Challenge of Handling Structured Missingness in Integrated Data Sources
Advanced Intelligent Discovery, EarlyView.As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson +6 more
wiley +1 more source