Results 91 to 100 of about 111,969 (307)

Modeling Nonstationary Financial Volatility with the R Package tvgarch

Journal of Statistical Software
Certain events can make the structure of volatility of financial returns to change, making it nonstationary. Models of time-varying conditional variance such as generalized autoregressive conditional heteroscedasticity (GARCH) models usually assume ...
Susana Campos-Martins, Genaro Sucarrat
doaj   +1 more source

Asymptotic near-efficiency of the “Gibbs-energy (GE) and empirical-variance” estimating functions for fitting Matérn models - II: Accounting for measurement errors via “conditional GE mean” [PDF]

, 2020
Didier Girard
openalex   +1 more source

Modeling price dynamics and risk Forecasting in Tehran Stock Exchange: Conditional Variance Heteroscedasticity Hidden Markov Models [PDF]

, 2023
Moslem Nilchi, Daryush Farid, Moslem Peymany, Hamidreza Mirzaei   +3 more
openalex   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Factors Driving Battery and Solar Purchase Decision of Residents: a Behavioural Choice Experiment Using a Hybrid Discrete Choice and Latent Variable Model

Advanced Sustainable Systems, EarlyView.
This article explores what drives households to adopt solar PV and battery systems in South East Queensland. Using hybrid discrete choice experiments, it reveals distinct adopter profiles and highlights cost, system size, and energy independence as key motivators.
Mohammad Alipour, Elnaz Irannezhad, Rodney A. Stewart, Oz Sahin   +3 more
wiley   +1 more source

Using Bayesian Optimization to Increase the Efficiency of III‐V Multijunction Solar Cells

Advanced Theory and Simulations, EarlyView.
Technology Computer Aided Design (TCAD) modeling is crucial for designing complex optoelectronic devices like III‐V multijunction solar cells. Bayesian optimization is proposed as a robust method to address challenges in optimizing costly black‐box TCAD solvers.
Pablo F. Palacios, Carlos Algora
wiley   +1 more source

Semiparametric Estimator of Time Series Conditional Variance

Journal of Business & Economic Statistics, 2010
We propose a new combined semiparametric estimator, which incorporates the parametric and nonparametric estimators of the conditional variance in a multiplicative way. We derive the asymptotic bias, variance, and normality of the combined estimator under general conditions.
MISHRA, Santosh, SU, Liangjun, ULLAH, Aman   +2 more
openaire   +4 more sources

ROS Activated NETosis of Bone Marrow CD55+ Intermediate Mature Neutrophils Through HIF1α‐PADI4 Pathway to Initiate Bone Aging

Advanced Science, EarlyView.
In this study, we find CD55+ neutrophils show activated NETosis within bone marrow, induce BMSC senescence and osteogenesis inhibition, finally leading to bone aging initiation. Mechanistically, ROS synergizes with the CD55‐driven HIF1α‐PADI4 pathway to promote NETosis.
Yutong Guo, Shengjie Cui, Xi Wen, Yidi Wang, Ben Wu, Yixiang Wang, Yan Gu   +6 more
wiley   +1 more source

Genome‐Wide by Lifetime Environment Interaction Studies of Brain Imaging Phenotypes

Advanced Science, EarlyView.
This study explores genome‐wide by lifetime environment interactions on brain imaging phenotypes. Gene‐environment interactions explain more phenotypic variance than main effects, pinpoint regulatory variants, and reveal exposure‐specific biological pathways.
Sijia Wang, Meiyun Wang, Peng Zhang, Jingliang Cheng, Longjiang Zhang, Wenzhen Zhu, Shijun Qiu, Zuojun Geng, Guangbin Cui, Yongqiang Yu, Weihua Liao, Xi‐Nian Zuo, Hui Zhang, Bo Gao, Xiaojun Xu, Tong Han, Zhenwei Yao, Quan Zhang, Feng Liu, Qiang Xu, Jiayuan Xu, Jilian Fu, Nana Liu, Yuan Ji, Jie Tang, Lining Guo, Mengge Liu, Xiaoxiao Xiao, Xiaoxuan Liu, Wei Li, Caihong Wang, Wei Wei, Dapeng Shi, Su Lui, Zhihan Yan, Feng Chen, Jing Zhang, Wen Shen, Yanwei Miao, Dawei Wang, Jia‐Hong Gao, Yunjun Yang, Kai Xu, Junfang Xian, Bing Zhang, Xiaochu Zhang, Zhaoxiang Ye, Le Yu, Wen Qin, Meng Liang, Chunshui Yu, the CHIMGEN Consortium   +51 more
wiley   +1 more source

Mettl3‐Mediated m6A Modification Represents a Novel Therapeutic Target for FSGS

Advanced Science, EarlyView.
This study explores the roles of Mettl3‐induced N6‐methyladenosine (m6A) modifications in Focal segmental glomerulosclerosis (FSGS). The findings reveal that inhibition of Mettl3 results in podocyte injury by modulating the TJP1CDC42 pathway. Moreover, Administration of N6‐methyladenosine attenuates the FSGS phenotype in WT mice induced by Adriamycin ...
Fubin Zhu, Hongzhi Li, Xiang Li, Chunxiu Du, Ting Wang, Xuling Zhou, Xiaobei Xie, Yunxia Shao, Yingzhi Huang, Yanling Hu, Xinxin Guo, Bin Zhu, Shanshan Yu, Xiaoyan Zhang, Binghai Zhao   +14 more
wiley   +1 more source