Results 91 to 100 of about 73,349 (260)

Performance Quantile Regression and Bayesian Quantile Regression in Dealing with Non-normal Errors (Case Study on Simulated Data)

Numerical: Jurnal Matematika dan Pendidikan Matematika
This research discusses the performance of quantile regression and Bayesian quantile regression methods. Quantile regression uses parameter estimation by maximizing the value of the likelihood function, while Bayesian quantile regression uses parameter ...
Lilis Harianti Hasibuan, Ferra Yanuar, Vika Pradinda Harahap, Latifatul Qalbi   +3 more
doaj   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

Quantile and quantile-function estimations under density ratio model

The Annals of Statistics, 2013
Published in at http://dx.doi.org/10.1214/13-AOS1129 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Chen, Jiahua, Liu, Yukun
openaire   +3 more sources

Uncertainty‐Aware Deep Ensembles for Robust and Reliable Chemical Sensor Arrays

Advanced Science, EarlyView.
A reliability‐aware electronic nose is developed using photothermally anchored metal‐catalyst decorated metal oxide nanofiber sensor arrays combined with deep ensemble learning. Diverse catalytic nanofiber channels generate gas‐specific response patterns, enabling selective identification and quantification of sulfur‐containing gases.
Sungwoo Eo, Ji‐Hwan Eum, Suk‐Jeong Kwon, Minji Sagong, Dongchan Kim, Dong‐Ha Kim   +5 more
wiley   +1 more source

Multivariate quantile inactivity time with medical applications

AIP Advances
The concept of α-quantile inactivity time was developed for situations with bivariate or multivariate random lifetimes. In this situation, each element has a specific history related to itself, indicating that the corresponding event occurred earlier ...
Mohamed Kayid
doaj   +1 more source

Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates

Advanced Science, EarlyView.
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao, Yufei Liu, Ruixi Huang, Zhongxue Gan, Siyang Leng   +4 more
wiley   +1 more source

Natural Variation of COLD and CATECHINS REGULATOR 1 Coordinately Fine‐Tunes Cold Tolerance and Tea Quality in Tea Plants

Advanced Science, EarlyView.
Multi‐trait genome‐wide association mapping identifies a central hub regulator, COLD AND CATECHINS REGULATOR 1 (CCR1), and its excellent natural allele variation, coordinately enhancing cold tolerance and promoting catechins biosyntheis. CsCCR1 interacts with CsCBF1/3 and is transcriptionally activated by CsLUX and CsKUA1 to promote catechins ...
Yanli Wang, Wei Tong, Qiong Wu, Didi Wu, Yanrui Zhang, Qijuan Gao, Fangdong Li, Zhaoliang Zhang, Wenjie Wang, Chuankui Song, Enhua Xia   +10 more
wiley   +1 more source

Quantile Approach of Dynamic Generalized Entropy (Divergence) Measure

Statistica, 2018
In the present paper, we propose a quantile version of generalized entropy measure for residual and past lifetimes and study their properties. Lower and upper bounds of the proposed measures are derived.
Vikas Kumar, Rekha Rani
doaj   +1 more source

Parametric Modeling of Quantile Regression Coefficient Functions

Biometrics, 2015
SummaryEstimating the conditional quantiles of outcome variables of interest is frequent in many research areas, and quantile regression is foremost among the utilized methods. The coefficients of a quantile regression model depend on the order of the quantile being estimated.
Frumento P, Bottai M
openaire   +4 more sources