Results 101 to 110 of about 2,902,077 (302)
Prediction of financial downside-risk with heavy-tailed conditional distributions [PDF]
, 2003 The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ...
Stefan Mittnik +4 more
core +1 more source
Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
On conditional truncated densities Bayesian networks
International Journal of Approximate Reasoning, 2018 The majority of Bayesian networks learning and inference algorithms rely on the assumption that all random variables are discrete, which is not necessarily the case in real-world problems. In situations where some variables are continuous, a trade-off between the expressive power of the model and the computational complexity of inference has to be done:
Cortijo, Santiago, Gonzales, Christophe
openaire +2 more sources
Augoregressive Conditional Kurtosis [PDF]
This paper proposes a new model for autoregressive conditional heteroscedasticity and kurtosis. Via a time-varying degrees of freedom parameter, the conditional variance and conditional kurtosis are permitted to evolve separately. The model uses only the
Simon P. Burke +2 more
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Flexible Sensors for Robotics Tactile Perception: A Review
Advanced Robotics Research, EarlyView.Flexible tactile sensing for robotics is reviewed through four interconnected dimensions. Physical mechanisms include piezoresistive, capacitive, piezoelectric, triboelectric, iontronic, and optical sensing. Structural design includes bioinspired, defect‐based, and MEMS‐based tactile systems.
Yu Song, Ying Chen, Yihao Chen, Xue Feng
wiley +1 more source
Modelling the Density of Inflation Using Autoregressive Conditional Heteroscedasticity, Skewness, and Kurtosis Models [PDF]
The paper aimed at modelling the density of inflation based on time-varying conditional variance, skewness and kurtosis model developed by Leon, Rubio, and Serna (2005) who model higher-order moments as GARCH-type processes by applying a Gram-Charlier ...
Doaa Akl Ahmed
core
Advanced Science, EarlyView.IGFBP4 is upregulated in granulosa cells of aged ovaries across monkeys, mice, and humans. It inhibits YAP signaling, thereby suppressing cell proliferation and contributing to follicular dysfunction. Deletion of Igfbp4 in granulosa cells enhances ovulatory output, improves hormone profiles, and reproductive performance in aged female mice, suggesting ...
Qianhui Hu +8 more
wiley +1 more source
An Extended Result on the Optimal Estimation Under the Minimum Error Entropy Criterion
Entropy, 2014 The minimum error entropy (MEE) criterion has been successfully used in fields such as parameter estimation, system identification and the supervised machine learning.
Badong Chen +3 more
doaj +1 more source
The density condition and the strong dual density condition by operator
Collectanea Mathematica, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
Noise Regularization for Conditional Density Estimation
CoRR, 2019 Modelling statistical relationships beyond the conditional mean is crucial in many settings. Conditional density estimation (CDE) aims to learn the full conditional probability density from data. Though highly expressive, neural network based CDE models can suffer from severe over-fitting when trained with the maximum likelihood objective.
Rothfuss, Jonas +6 more
openaire +3 more sources