Results 191 to 200 of about 333,475 (312)

Identification of the Most Stable Durum Wheat Genotypes Using Nonparametric Yield Stability Statistics [PDF]

, 2019
Rahmatollah Karımızadeh, Ali Asghari, Omid Sofalian, Kamal Shahbazi Homonlo, Tahmaseb Hossienpour, Hasan Ghojogh, Mohammad Armion   +6 more
openalex   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

A New Approach to the Nonparametric Behrens-Fisher Problem With Compatible Confidence Intervals. [PDF]

Biom J
Schüürhuis S, Konietschke F, Brunner E.   +2 more
europepmc   +1 more source

A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

Advanced Intelligent Discovery, EarlyView.
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai, Wenrui Wang, Rui Chen, Tong Yu, Xiaojuan Zheng, Hua Shao, Dashan Shang, Ling Li, Lado Filipovic   +8 more
wiley   +1 more source

Nonparametric Bayesian Adjustment of Unmeasured Confounders in Cox Proportional Hazards Models. [PDF]

Stat Med
Orihara S, Sugasawa S, Ohigashi T, Hirano K, Nakagawa T, Taguri M.   +5 more
europepmc   +1 more source

Method of probability calculation of rolling bearing durability based on apparatus of nonparametric statistics

, 2022
K. V. Syzrantseva, Lyudmila Fetisova, Alina A. Beloborodova   +2 more
openalex   +1 more source

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, Marius Hofert, Eleni‐Rosalina Andrinopoulou, Niels Hagenbuch, Sarah McGough, Chris Harbron, Robin Mitra   +6 more
wiley   +1 more source

A Methodological Review of Simulation Studies Published in Pharmacoepidemiology and Drug Safety. [PDF]

Pharmacoepidemiol Drug Saf
Muddiman R, Battan FIA, Tazare J, Schultze A, Boland F, Perez T, Wei L, Walsh ME, Moriarty F.   +8 more
europepmc   +1 more source

Random positive linear operators and their applications to nonparametric statistics [PDF]

José A. Adell, José Tomás Alcalá Nalvaiz, C. Sangüesa   +2 more
openalex  

Relative-Error Prediction in Nonparametric Functional Statistics: Theory and Practice

, 2015
Jacques Demongeot, Ali Hamié, Ali Laksaci, Mustapha Rachdi   +3 more
openalex   +1 more source