Results 61 to 70 of about 24,864 (292)

Multicollinearity and A Ridge Parameter Estimation Approach [PDF]

, 2016
One of the main goals of the multiple linear regression model, Y = Xβ + u, is to assess the importance of independent variables in determining their predictive ability.
Iguernane, Mohamed, Khalaf, Ghadban
core   +2 more sources

Microwave‐Assisted Aqueous Synthesis of Gelatin‐Norbornene for Hydrogel Crosslinking and Bioprinting

Advanced Materials Technologies, EarlyView.
A microwave‐assisted reaction is utilized to synthesize gelatin‐norbornene (GelNB), achieving a high degree of norbornene functionalization while reducing the macromer's upper critical solution temperature. The resulting GelNB macromer has high solubility at room temperature, facilitating light‐based 3‐dimensional (3D) printing of thiol‐norbornene ...
Jonathan B. Bryan, Chien‐Chi Lin
wiley   +1 more source

PEMODELAN UPAH MINIMUM KABUPATEN/KOTA DI JAWA TENGAH BERDASARKAN FAKTOR-FAKTOR YANG MEMPENGARUHINYA MENGGUNAKAN REGRESI RIDGE [PDF]

, 2016
The least squares method is a regression parameter estimation method for simple linear regression and multiple linear regression. This method produces no bias and variance estimator minimum if no multicollinearity.
HILDAWATI, HILDAWATI
core   +2 more sources

Special ridge-type estimator: Simulation and application to chemical data

AIP Advances
This study delves into regularization techniques, such as ridge regression, Liu estimator, and Kibria–Lukman estimator, as alternatives to the maximum likelihood method for addressing multicollinearity in beta regression models.
Rasha A. Farghali, Adewale F. Lukman, Haadi Abdul-Rahaman, Zakariya Yahya Algamal, Samah M. Abo-El-Hadid   +4 more
doaj   +1 more source

A New Type Iterative Ridge Estimator: Applications and Performance Evaluations

Journal of Mathematics, 2022
The usage of the ridge estimators is very common in presence of multicollinearity in multiple linear regression models. The ridge estimators are used as an alternative to ordinary least squares in case of multicollinearity as they have lower mean square ...
Aydın Karakoca
doaj   +1 more source

Risk Convergence of Centered Kernel Ridge Regression with Large Dimensional Data

, 2019
This paper carries out a large dimensional analysis of a variation of kernel ridge regression that we call \emph{centered kernel ridge regression} (CKRR), also known in the literature as kernel ridge regression with offset.
Al-Naffouri, Tareq, Alouini, Mohamed-Slim, Elkhalil, Khalil, Kammoun, Abla, Zhang, Xiangliang   +4 more
core   +1 more source

Lattice Structures for Bone Replacement: The Intersection of Bone Biomechanics, Lattice Design, and Additive Manufacturing

Advanced Materials Technologies, EarlyView.
This review outlines how understanding bone's biology, hierarchical architecture, and mechanical anisotropy informs the design of lattice structures that replicate bone morphology and mechanical behavior. Additive manufacturing enables the fabrication of orthopedic implants that incorporate such structures using a range of engineering materials ...
Stylianos Kechagias, Maxwell J. Munford, Frederik C.H. Masure, Richard J. van Arkel, Reece N Oosterbeek   +4 more
wiley   +1 more source

Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers [PDF]

, 2015
This study presents an improvement to robust ridge regression estimator. We proposed two methods Bisquare ridge least trimmed squares (BRLTS) and Bisquare ridge least absolute value (BRLAV) based on ridge least trimmed squares RLTS and ridge least ...
Adnan, Robiah, Kafi, Dano Pati, Md. Jedi, Muhamad Alias, Rasheed, Abdulkadir Bello   +3 more
core   +1 more source

Ductility Tuning via Cluster Network Characteristics of Porous Components

Advanced Materials Technologies, EarlyView.
Network optimization via cluster characteristics induced by interaction of stress concentration is proposed, demonstrating increased cluster size and dispersion in non‐uniform porous components. The optimized structures exhibit, for the first time, that enhanced ductility and damage progression is controllable through zigzag cluster network designed by
Ryota Toyoba, Yuichi Otsuka, Ian J Davies, Naritoshi Aoyagi, Yukio Miyashita   +4 more
wiley   +1 more source

Bootstrap-quantile ridge estimator for linear regression with applications.

PLoS ONE
Bootstrap is a simple, yet powerful method of estimation based on the concept of random sampling with replacement. The ridge regression using a biasing parameter has become a viable alternative to the ordinary least square regression model for the ...
Irum Sajjad Dar, Sohail Chand
doaj   +2 more sources