Results 31 to 40 of about 8,872 (261)

Asymptotic normality of extensible grid sampling [PDF]

Statistics and Computing, 2017
Recently, He and Owen (2016) proposed the use of Hilbert's space filling curve (HSFC) in numerical integration as a way of reducing the dimension from $d>1$ to $d=1$. This paper studies the asymptotic normality of the HSFC-based estimate when using scrambled van der Corput sequence as input.
Zhijian He, Lingjiong Zhu
openaire   +3 more sources

A Conway–Maxwell–Poisson-Binomial AR(1) Model for Bounded Time Series Data

Entropy, 2023
Binomial autoregressive models are frequently used for modeling bounded time series counts. However, they are not well developed for more complex bounded time series counts of the occurrence of n exchangeable and dependent units, which are becoming ...
Huaping Chen, Jiayue Zhang, Xiufang Liu
doaj   +1 more source

Molecular dynamics simulations of positively selected codons in FcγRI reveal novel biochemical binding properties

FEBS Open Bio, EarlyView.
Evolutionary analysis across 32 placental mammals identified positive selection at residues H148 and W149 in the immune receptor FcγR1. Ancestral reconstruction combined with molecular dynamics simulations reveals how these mutations may influence receptor structure and dynamics, providing insight into the evolution of antibody recognition and immune ...
David A. Young, Omar Arias‐Gaguancela, Fiona Gibson, Morgan Grainger, Jodie Score, Amit Nathubhai, Mauricio Cafiero, Lee Richard Machado   +7 more
wiley   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Discretization and Asymptotic Normality of Drift Parameters Estimator in the Cox-Ingersoll-Ross Model

Austrian Journal of Statistics
This paper investigates the simultaneous estimation of two drift parameters of a Cox-Ingersoll-Ross (CIR) model, for which observations can be made either continuously or at discrete time instants.
Olha Prykhodko, Kostiantyn Ralchenko
doaj   +1 more source

Integral Least-Squares Inferences for Semiparametric Models with Functional Data

Journal of Applied Mathematics, 2014
The inferences for semiparametric models with functional data are investigated. We propose an integral least-squares technique for estimating the parametric components, and the asymptotic normality of the resulting integral least-squares estimator is ...
Limian Zhao, Peixin Zhao
doaj   +1 more source

Karl Popper and the Mechanisms of Hydrogen Embrittlement

Advanced Engineering Materials, EarlyView.
Representation of the beginning of loss of ductility rather than embrittlement. Small concentrations of hydrogen in a diffusible form within iron are well‐established to harm the mechanical integrity of steels. There are theories that attempt to explain the pernicious role of hydrogen.
H. K. D. H. Bhadeshia
wiley   +1 more source

From Shear to Sound: Mechanics–Acoustics Mapping of TPMS Lattices

Advanced Engineering Materials, EarlyView.
Triply periodic minimal surface (TPMS) lattices are mapped across mechanical and acoustic performance, revealing that descriptors validated in compression fail under shear. First‐time comparison with trusses included. A transition from porous to resonance‐driven absorption emerges at 25% density.
Lucía Doyle, María Ángeles Navacerrada, Johan Christensen, Carlos González   +3 more
wiley   +1 more source

Asymptotic normality and mean consistency of LS estimators in the errors-in-variables model with dependent errors

Open Mathematics, 2020
In this article, an errors-in-variables regression model in which the errors are negatively superadditive dependent (NSD) random variables is studied. First, the Marcinkiewicz-type strong law of large numbers for NSD random variables is established. Then,
Zhang Yu, Liu Xinsheng, Yu Yuncai, Hu Hongchang   +3 more
doaj   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source