Results 81 to 90 of about 44,356 (305)

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

Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models

Complexity, 2020
We propose a high-dimensional copula to model the dependence structure of the seemingly unrelated quantile regression. As the conventional model faces with the strong assumption of the multivariate normal distribution and the linear dependence structure,
Nachatchapong Kaewsompong, Paravee Maneejuk, Woraphon Yamaka   +2 more
doaj   +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

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

The Impact of the 2016 EU Audit Reforms, Oversight, and Corruption on Earnings Management: Evidence From European Banks Using a Dynamic Panel Approach

International Journal of Finance &Economics, EarlyView.
ABSTRACT This study investigates earnings management in European banks in the context of the 2016 EU audit directive. Using a dynamic panel of 134 banks over 2012–2023, we apply two‐step System‐GMM estimators with three profitability measures—Earnings Before Provisions and Taxes (EBPT), Return on Assets (ROA), and Return on Equity (ROE).
Maria Christofidou, Epameinondas Katsikas, Dimitrios Koufopoulos, Konstantinos Spanos   +3 more
wiley   +1 more source

From Reactive to Proactive Volatility Modeling With Hemisphere Neural Networks

Journal of Applied Econometrics, EarlyView.
ABSTRACT We revisit maximum likelihood estimation (MLE) for macroeconomic density forecasting through a novel neural network architecture with dedicated mean and variance hemispheres. Our architecture features several key ingredients making MLE work in this context.
Philippe Goulet Coulombe, Mikael Frenette, Karin Klieber   +2 more
wiley   +1 more source

Bayesian quantile regression for longitudinal count data

Journal of Statistical Computation and Simulation, 2022
This work introduces Bayesian quantile regression modeling framework for the analysis of longitudinal count data. In this model, the response variable is not continuous and hence an artificial smoothing of counts is incorporated. The Bayesian implementation utilizes the normal-exponential mixture representation of the asymmetric Laplace distribution ...
openaire   +2 more sources

Machine Learning Prediction of Raster Angle Effects on Mechanical Properties of Extrusion‐Based Additively Manufactured Conductive Thermoplastic Polyurethane Composites

Macromolecular Materials and Engineering, EarlyView.
This study integrates machine learning (ML) and high‐fidelity experiments to model how raster angle influences the mechanical properties of fused filament fabricated conductive TPU composites. Using Poly6 and SVR models, the approach accurately predicts stiffness, strength, and ductility.
Imran Khan, Ans Al Rashid, Muammer Koç
wiley   +1 more source

Short-term Traffic Flow Prediction Method in Bayesian Networks Based on Quantile Regression

Promet (Zagreb), 2020
With the popularization of intelligent transportation system and Internet of vehicles, the traffic flow data on the urban road network can be more easily obtained in large quantities. This provides data support for shortterm traffic flow prediction based
Jing Luo
doaj   +1 more source

Childhood exposures to environmental chemicals and neurodevelopmental outcomes in congenital heart disease.

PLoS ONE, 2022
BackgroundChildren with congenital heart defects have an increased risk of neurodevelopmental disability. The impact of environmental chemical exposures during daily life on neurodevelopmental outcomes in toddlers with congenital heart defects is unknown.
J William Gaynor, Nancy B Burnham, Richard F Ittenbach, Marsha Gerdes, Judy C Bernbaum, Elaine Zackai, Daniel J Licht, William W Russell, Erin E Zullo, Thomas Miller, Hakon Hakonarson, Kayan A Clarke, Gail P Jarvik, Antonia M Calafat, Asa Bradman, David C Bellinger, Frederick M Henretig, Eric S Coker   +17 more
doaj   +1 more source