Results 61 to 70 of about 91,409 (256)

Experiencias con un nuevo índice de falta de ajuste en Tablas de Contingencia

Revista de Matemática: Teoría y Aplicaciones, 2012
Rudas, Clogg and Lindsay, en 1994, proposed a new index of lack of fit for contingency table analysis. For a contingency table P with N cells, and a model H, the new index is defined as the smallest \pi that satisfies the equation P_h=(1-\pi)\Pi_{1h ...
Adalberto González Debén, Ignacio Méndez Ramírez   +1 more
doaj   +1 more source

Haplotype‐Resolved 3D Genomic Landscapes and Their Impacts on Agronomic Traits in Grapevine

Advanced Science, EarlyView.
This study presents a haplotype‐resolved 3D genomic landscape of grapevine, revealing that structural variations (SVs) are closely associated with phased topologically associating domain (TAD) boundary transitions. These rearrangements coordinate with allele‐specific DNA methylation (ASM) and allele‐biased gene expression (ASE) to shape key agronomic ...
Yanling Peng, Lianzhu Zhou, Xinyue Fang, Ruoyan Zhao, Qi Xu, Mengrui Du, Ting Hou, Guizhou Huang, Yingchun Zhang, Sheng Yan, Ruo Yang, Zhongxin Jin, Yang Dong, Yanshuai Xu, Hua Xiao, Xiaodong Xu, Yi Liao, Xiping Wang, Yongfeng Zhou   +18 more
wiley   +1 more source

Contingency, Gender, and the Academic Table

Journal of Moral Theology, 2019
This essay examines the marginalization of contingent voices in the academy as it intersects with the gendered nature of such contingency. My claim is that the exclusion of contingent voices from full participation in our academic institutions ultimately
Karen Peterson-Iyer
doaj  

Partial Information Releases for Confidential Contingency Table Entries: Present and Future Research Efforts

The Journal of Privacy and Confidentiality, 2010
Tabular data have been a staple product for disseminating information derived from the confidential microdata that fuel social science research and inform policy decisions. This paper outlines recent results on disclosure risk assessment associated with
Aleksandra B. Slavkovic
doaj   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Pathological Findings in Hanging: Is the Traditional Knowledge Correct?

Diagnostics
Background: In forensic pathology, asphyxia presents a problem as frequently as it is thorny and challenging. Some knowledge in forensic pathology is still considered to be traditionally acquired and is not critically assessed with modern statistical or ...
Graziano Domenico Luigi Crudele, Alberto Amadasi, Lorenzo Franceschetti, Cristina Cattaneo   +3 more
doaj   +1 more source

Profile Statistics for Sparse Contingency Tables under Poisson Sampling

Austrian Journal of Statistics, 2016
Simple conditions for the inconsistency of classical likelihood ratio (LR) test in case of very sparse categorical data are given. The LR type test based on profile statistics is proposed as an alternative.
Marijus Radavičius, Pavel Samusenko
doaj   +1 more source

The quantification of Simpson's paradox and other contributions to contingency table theory. [PDF]

PLoS One, 2022
Teuscher F.
europepmc   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Decoupling Intrinsic Molecular Efficacy From Platform Effects: An Interpretable Machine Learning Framework for Unbiased Perovskite Passivator Discovery

Advanced Science, EarlyView.
This study establishes an interpretable machine learning framework that disentangles the intrinsic molecular efficacy of passivators from experimental platform effects—enabling unbiased, high‐throughput discovery of effective perovskite surface modifiers.
Jing Zhang, Ziyuan Li, Shan Gao, Zhen Zhu, Jing Wang, Xiangmei Duan   +5 more
wiley   +1 more source