Results 71 to 80 of about 10,357 (300)

Modeling T20I cricket bowling effectiveness: A quantile regression approach with a Bayesian extension

Journal of Sports Analytics, 2021
Bowling effectiveness is a key factor in winning cricket matches. The team captain should decide when to use the right bowler at the right moment so that the team can optimize the outcome of the game.
Sulalitha M.B. Bowala, Ananda B.W. Manage, Stephen M. Scariano   +2 more
doaj   +1 more source

Point and Risk estImation Using an enSemble of Models for Nowcasting: PRISM‐Now

Journal of Forecasting, EarlyView.
ABSTRACT We propose PRISM‐Now, a novel ensemble forecasting system for near‐term GDP projection. Recognizing that relevant economic information evolves over time, we treat forecasts from multiple base models as draws from a mixture distribution of “good” and “bad” estimates, whose composition changes continuously and cannot be identified ex ante.
Beomseok Seo, Hyungbae Cho, Dongjae Lee
wiley   +1 more source

Variational Bayesian Quantile Regression with Non-Ignorable Missing Response Data

Axioms
For non-ignorable missing response variables, the mechanism of whether the response variable is missing can be modeled through logistic regression. In Bayesian computation, the lack of a conjugate prior for the logistic function poses a significant ...
Juanjuan Zhang, Weixian Wang, Maozai Tian   +2 more
doaj   +1 more source

Retirement Consumption Puzzle in Malaysia: Evidence from Bayesian Quantile Regression Model

Journal of Probability and Statistics, 2019
The objective of this study is to use the Bayesian quantile regression for studying the retirement consumption puzzle, which is defined as the drop in consumption upon retirement, using the cross-sectional data of the Malaysian Household Expenditure ...
Ros Idayuwati Alaudin, Noriszura Ismail, Zaidi Isa   +2 more
doaj   +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

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

Bayesian quantile estimation and regression with martingale posteriors [PDF]

Journal of the Royal Statistical Society Series B: Statistical Methodology
Abstract Quantile estimation and regression within the Bayesian framework is challenging as the choice of likelihood and prior is not obvious. In this paper, we introduce a novel Bayesian nonparametric method for quantile estimation and regression based on the recently introduced martingale posterior (MP) framework.
Fong, Edwin, Yiu, Andrew
openaire   +2 more sources

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

Migration‐Associated Variation in Gastric Cancer Risk in the United States: Implications for Risk Stratification

International Journal of Cancer, EarlyView.
This study provides contemporary, population‐based evidence that migration‐associated differences in gastric cancer risk, first described decades ago, remain stable, quantifiable, and prevention‐relevant in the United States. By integrating modern cancer registry data with formal trend analysis and conditional extrapolation, the authors show that ...
Chul S. Hyun, Rong Wang, Sung Hwi Hong, Xuehong Zhang, Jae Il Shin   +4 more
wiley   +1 more source

Bayesian Quantile Regression for Partial Functional Linear Spatial Autoregressive Model

Axioms
When performing Bayesian modeling on functional data, the assumption of normality is often made on the model error and thus the results may be sensitive to outliers and/or heavy tailed data.
Dengke Xu, Shiqi Ke, Jun Dong, Ruiqin Tian   +3 more
doaj   +1 more source