Results 71 to 80 of about 25,397 (329)
A Comparison between Biased and Unbiased Estimators in Ordinary Least Squares Regression [PDF]
During the past years, different kinds of estimators have been proposed as alternatives to the Ordinary Least Squares (OLS) estimator for the estimation of the regression coefficients in the presence of multicollinearity. In the general linear regression
Khalaf, Ghadban
core +2 more sources
Study of a Novel Bi‐Layered Thermoplastic Polyurethane Patch for Congenital Diaphragmatic Hernia
Large congenital diaphragmatic hernia remains a challenge due to the poor compatibility of current prostheses. To tackle this problem, a bilayer thermoplastic polyurethane patch with tunable mechanical properties is engineered, whose fibrous side supports rapid fibroblast and myoblast colonization, while the smooth film limits adhesions.
Guillaume Leks +14 more
wiley +1 more source
Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers [PDF]
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 +3 more
core +1 more source
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 +4 more
wiley +1 more source
PEMODELAN UPAH MINIMUM KABUPATEN/KOTA DI JAWA TENGAH BERDASARKAN FAKTOR-FAKTOR YANG MEMPENGARUHINYA MENGGUNAKAN REGRESI RIDGE [PDF]
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
Handling multicollinearity and outliers using weighted ridge least trimmed squares [PDF]
Common problems in multiple linear regression models are multicollinearity and outliers. In this paper, we will propose a robust ridge regression. It is based on weighted ridge least trimmed squares (WRLTS).
Adnan, Robiah +3 more
core
Ductility Tuning via Cluster Network Characteristics of Porous Components
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 +4 more
wiley +1 more source
Multi-task Regression using Minimal Penalties [PDF]
In this paper we study the kernel multiple ridge regression framework, which we refer to as multi-task regression, using penalization techniques. The theoretical analysis of this problem shows that the key element appearing for an optimal calibration is ...
Arlot, Sylvain +2 more
core +6 more sources
Recent Advances of Slip Sensors for Smart Robotics
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 +8 more
wiley +1 more source
Regression analysis is one of the statistical methods used to determine the causal relationship between one or more explanatory variables to the affected variable.
Gustina Saputri +3 more
doaj +1 more source

