Results 91 to 100 of about 76,877 (313)
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 +5 more
wiley +1 more source
EFEKTIVITAS REGRESI KUANTIL DALAM MENGATASI PONTENSIAL PENCILAN
Barekeng, 2020 Quantile regression as a robust regression method can be used to overcome the impact of unusual cases on regression estimates such as the presence of potential outliers in the data.
Netti Herawati
doaj +1 more source
Using Quantile Regression for Duration Analysis [PDF]
Quantile regression methods are emerging as a popular technique in econometrics and biometrics for exploring the distribution of duration data. This paper discusses quantile regression for duration analysis allowing for a flexible specification of the ...
Wilke, Ralf A., Fitzenberger, Bernd
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A partially collapsed Gibbs sampler for Bayesian quantile regression [PDF]
, 2009 We introduce a set of new Gibbs sampler for Bayesian analysis of quantile re-gression model. The new algorithm, which partially collapsing an ordinary Gibbs sampler, is called Partially Collapsed Gibbs (PCG) sampler.
Yu, K, Reed, C, Keming Yu, Craig Reed
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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 +4 more
wiley +1 more source
Quantile Regression Learning with Coefficient Dependent lq-Regularizer
MATEC Web of Conferences, 2018 In this paper, We focus on conditional quantile regression learning algorithms based on the pinball loss and lq-regularizer with 1≤q≤2. Our main goal is to study the consistency of this kind of regularized quantile regression learning. With concentration
Sun Pengju, Li Meng, Sun Hongwei
doaj +1 more source
Advanced Science, EarlyView.Lipoic acid synthase (lias) can regulate α‐KG levels through lipoylation, thereby negatively regulating HIF‐1α protein levels via PHD under hypoixa. The Hap2 allele of lias exhibits lower expression levels than Hap1, leading to the accumulation of more HIF‐1α protein and thereby enhancing hypoxia tolerance. ABSTRACT Hypoxia stress seriously affects the
Jie Ding +7 more
wiley +1 more source
Advanced Science, EarlyView.Large‐scale UK Biobank analyses identify clinical and proteomic signatures for early prediction of valvular heart disease and its subtypes. Proteins add predictive value for VHD, AVS, and MVR, with outcome‐specific compact panels showing translational potential. Multi‐layer evidence highlights matrix remodeling, protease regulation, immune inflammation,
Zhihao Jiang +10 more
wiley +1 more source
Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression
Risks, 2017 Measuring interdependence between probabilities of default (PDs) in different industry sectors of an economy plays a crucial role in financial stress testing. Thereby, regression approaches may be employed to model the impact of stressed industry sectors
Matthias Fischer +3 more
doaj +1 more source
Applied Economic Perspectives and Policy, EarlyView.ABSTRACT Rice is the main staple food for more than half of the world's population and the income from rice is an essential source for livelihoods of millions of households. We examine whether direct seed in rice production is an adaptation of rice farmers to rainfall changes and farm labor scarcity.
Manh Hung Do
wiley +1 more source