Results 61 to 70 of about 307,922 (236)

Histopathologic Analysis of the Morpho‐Functional Zones of the Human Acetabular Labrum

Clinical Anatomy, EarlyView.
ABSTRACT The structural and functional adaptation of soft tissues to mechanical load controls their ability to withstand injury and influences their capacity for healing. Similar to the knee meniscus, the acetabular labrum exhibits zonal differences in mechanical load distribution, resulting in distinct regions with unique structural and functional ...
Abdulaziz A. Alomiery, Andrew C. Hall, Thomas H. Gillingwater, Afaf Alsolami, Abduelmenem Alashkham   +4 more
wiley   +1 more source

Relation Between Asymptotic $L_p$-Convergence and Some Classical Modes of Convergence

Real Analysis Exchange
Asymptotic $L_p$-convergence, which resembles convergence in $L_p$, was introduced to address a question in diffusive relaxation. This note aims to compare asymptotic $L_p$-convergence with convergence in measure and in weak $L_p$ spaces. One of the results characterizes convergence in measure on finite measure spaces in terms of asymptotic $L_p ...
Alves, Nuno J., Oniani, Giorgi G.
openaire   +3 more sources

The Impact of Self‐Checkout Technology on Shopping Behavior in B2B Retail: Evidence From Point‐Of‐Sale Transaction Data

Journal of Consumer Behaviour, EarlyView.
ABSTRACT This study examines the impact of self‐checkout technology implementation on B2B customer shopping behavior using a novel methodological approach that combines propensity score matching with difference‐in‐differences analysis on actual point‐of‐sale transaction data.
Jindřich Špička, Michaela Dvořáková   +1 more
wiley   +1 more source

The Future of Foundation Machine Learning Potentials and DFT in Homogeneous Catalysis: Competition or Synergy?

Chemistry – A European Journal, EarlyView.
Machine‐learning potentials are increasingly taking on the exploratory tasks of homogeneous catalysis, enabling rapid conformer sampling and reaction‐space mapping. However, when selectivity depends on subtle electronic effects, electronic‐structure methods remain essential.
Maxime Ferrer, Julen Munarriz, Thijs Stuyver, Ruben Laplaza   +3 more
wiley   +1 more source

Restricted Tweedie stochastic block models

Canadian Journal of Statistics, EarlyView.
Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley   +1 more source

Rank‐based estimation of propensity score weights via subclassification

Canadian Journal of Statistics, EarlyView.
Abstract Propensity score (PS) weighting estimators are widely used for causal effect estimation and enjoy desirable theoretical properties, such as consistency and potential efficiency under correct model specification. However, their performance can degrade in practice due to sensitivity to PS model misspecification.
Linbo Wang, Yuexia Zhang, Thomas S. Richardson, Xiaohua Zhou   +3 more
wiley   +1 more source

On subset least squares estimation and prediction in vector autoregressive models with exogenous variables

Canadian Journal of Statistics, EarlyView.
Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne, Thanh‐Liem Huynh, Mylène Oscar   +2 more
wiley   +1 more source

Asymptotic properties of cross‐classified sampling designs

Canadian Journal of Statistics, EarlyView.
Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley   +1 more source

Bayesian inverse ensemble forecasting for COVID‐19

Canadian Journal of Statistics, EarlyView.
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley   +1 more source

A goodness‐of‐fit test for regression models with discrete outcomes

Canadian Journal of Statistics, EarlyView.
Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang, Christian Genest, Johanna G. Nešlehová   +2 more
wiley   +1 more source