Results 81 to 90 of about 19,694 (357)

Volatility analysis and forecasting of vegetable prices using an ARMA‐GARCH model: An application of the CF filter and seasonal adjustment method to Korean green onions

Agribusiness, EarlyView.
Abstract The vegetable market experiences significant price fluctuations due to the complex interplay of trend, cyclical, seasonal, and irregular factors. This study takes Korean green onions as an example and employs the Christiano–Fitzgerald filter and the CensusX‐13 seasonal adjustment methods to decompose its price into four components: trend ...
Yiyang Qiao, Byeong‐il Ahn
wiley   +1 more source

Moment convergence rates in the law of iterated logarithm for moving average process under dependence

Journal of Inequalities and Applications, 2016
We assume that X k = ∑ i = − ∞ + ∞ a i ξ i + k $X_{k}=\sum_{i=-\infty}^{+\infty}a_{i}\xi_{i+k}$ is a moving average process and { ξ i , − ∞ < i < + ∞ } $\{\xi_{i},-\infty ...
Yayun Zhang, Qunying Wu
doaj   +1 more source

On the Law of the Iterated Logarithm

The Annals of Probability, 1974
A triumvirate of sufficient conditions is given for unbounded, independent random variables to obey the Law of the Iterated Logarithm (LIL). As special cases, new results for weighted i.i.d. random variables and the Hartman-Wintner theorem are obtained.
openaire   +3 more sources

Functional Limit Theorems for Multiparameter Fractional Brownian Motion

, 2004
We prove a general functional limit theorem for multiparameter fractional Brownian motion. The functional law of the iterated logarithm, functional L\'{e}vy's modulus of continuity and many other results are its particular cases.
A. Benassi, A. Erdeélyi, A. Khintchin, A.P. Prudnikov, A.P. Prudnikov, A.P. Prudnikov, Anatoliy Malyarenko, C. Mueller, D. Monrad, H. Oodaira, H. Oodaira, K. Dzhaparidze, M.A. Lifshits, M.I. Yadrenko, N. Gantert, N.Ya. Vilenkin, P. Lévy, V. Strassen   +17 more
core   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source

Elastic Fast Marching Learning from Demonstration

Advanced Intelligent Systems, EarlyView.
This article presents Elastic Fast Marching Learning (EFML), a novel approach for learning from demonstration that combines velocity‐based planning with elastic optimization. EFML enables smooth, precise, and adaptable robot trajectories in both position and orientation spaces.
Adrian Prados, Brendan Hertel, Ramon Barber, Reza Azadeh   +3 more
wiley   +1 more source

A Law of Iterated Logarithm on Lamplighter Diagonal Products [PDF]

, 2022
Gideon Amir, Guy Blachar
openalex   +1 more source

A CRDNet‐Based Watermarking Algorithm for Fused Visible–Infrared Images

Advanced Intelligent Systems, EarlyView.
CRDnet includes encoders and decoders based on residual and dense structures, a fusion network robust to 12 visible and infrared image fusion algorithms, and predictors for predicting watermarked infrared images. The encoder and decoder incorporate preprocessing steps, attention mechanisms, and activation functions suitable for infrared images.
Yu Bai, Li Li, Shanqing Zhang, Ting Luo, Chin‐Chen Chang   +4 more
wiley   +1 more source

Laws of the iterated logarithm for iterated perturbed random walks

Modern Stochastics: Theory and Applications
Let ${({\xi _{k}},{\eta _{k}})_{k\ge 1}}$ be independent identically distributed random vectors with arbitrarily dependent positive components and ${T_{k}}:={\xi _{1}}+\cdots +{\xi _{k-1}}+{\eta _{k}}$ for $k\in \mathbb{N}$. The random sequence ${({T_{k}}
Oksana Braganets
doaj   +1 more source