Results 31 to 40 of about 1,043 (255)

Boosting Correlation Based Penalization in Generalized Linear Models [PDF]

, 2007
In high dimensional regression problems penalization techniques are a useful tool for estimation and variable selection. We propose a novel penalization technique that aims at the grouping effect which encourages strongly correlated predictors to be in ...
Tutz, Gerhard, Ulbricht, Jan
core   +1 more source

On the biased Two-Parameter Estimator to Combat Multicollinearity in Linear Regression Model

African Scientific Reports, 2022
The most popularly used estimator to estimate the regression parameters in the linear regression model is the ordinary least-squares (OLS). The existence of multicollinearity in the model renders OLS inefficient.
Janet Iyabo Idowu, Olasunkanmi James Oladapo, Abiola Timothy Owolabi, Kayode Ayinde   +3 more
doaj   +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

On the Performance of Principal Component Liu-Type Estimator under the Mean Square Error Criterion

Journal of Applied Mathematics, 2013
Wu (2013) proposed an estimator, principal component Liu-type estimator, to overcome multicollinearity. This estimator is a general estimator which includes ordinary least squares estimator, principal component regression estimator, ridge estimator, Liu ...
Jibo Wu
doaj   +1 more source

Mean squared error comparisons of the modified ridge regression estimator and the restricted ridge regression estimator

, 1998
Swindel (1976) introduced a modified ndge regression estimator based on prior information. Sarkar (1992) suggested a new estimator by combining in a particular way the two approaches followed in obtaining the restricted least squares and ordinary ridge ...
Kaçiranlar S., Akdeniz F., Sakallioglu S.   +2 more
core   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Performance Evaluation of Measures of Central Tendency (MCT) in Tackling Missing Data in Collinear Regressors: A Comparison of Linear Estimators [PDF]

The Egyptian Statistical Journal
The presence of missing data and multicollinearity in regression analysis poses significant challenges to the reliability and accuracy of model estimates.
Abass Taiwo, Oluwatobi Ogunnusi, Timothy Olatayo, Biodun Efuwape   +3 more
doaj   +1 more source

Machine Learning Accelerated Computational Design of Bio‐Inspired Catalysts in the Nitrogen Reduction Reaction

Advanced Materials, EarlyView.
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano, Zihan You, Haoran Chen, Qifan Zhong, Rong‐Zhen Liao, Shaoqi Zhan   +5 more
wiley   +1 more source

Modeling energy content of municipal solid waste based on proximate analysis: R-k class estimator approach

Cogent Engineering, 2022
In the Ilorin metropolis, there are power challenges. Energy supplied by Power Holding Company of Nigeria is insufficient for the social, technological, and industrial requirements of the metropolis.
Rotimi Adedayo Ibikunle, Adewale Folaranmi Lukman, Isaac Femi Titiladunayo, Abdul-Rahaman Haadi   +3 more
doaj   +1 more source

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang, Liao Wu, Shuai He, Zhao Sha, Yuwan Huang, Shuying Wu, Dewei Chu, Chun H. Wang, Shuhua Peng   +8 more
wiley   +1 more source