Article
Mathematics, Applied
Leonardo Barrios Blanco, Paulo Henrique Ferreira, Francisco Louzada, Diego Carvalho do Nascimento
Summary: This study used a Bayesian methodology to probabilistically estimate the positions of Chilean Premier League teams, treating them as a hierarchical structure. The model was able to predict the league table accurately for the top five positions, with some small shifts in positions 6-11 due to similar expected number of goals. The findings suggest that the model is competitive for soccer championship prediction.
Article
Food Science & Technology
Alberto Garre, Marcel H. Zwietering, Martinus A. J. S. van Boekel
Summary: The proposed Most Probable Curve (MPC) method provides a reliable approach for fitting microbial inactivation models, especially for datasets with low or zero counts, offering a more realistic description of uncertainty and reducing uncertainty in primary model parameters.
INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY
(2022)
Article
Statistics & Probability
Andrea Gabrio
Summary: Statistical modelling of sports data has become increasingly popular in recent years, with different models proposed for various objectives such as identifying key characteristics for team success and predicting game outcomes or team rankings. In this study, a Bayesian hierarchical model is introduced to predict the rankings of volleyball national teams and estimate match results, with two alternative model specifications of different complexity validated using data from the Italian women's volleyball Serie A1 2017-2018 season.
JOURNAL OF APPLIED STATISTICS
(2021)
Article
Mathematical & Computational Biology
Armando Turchetta, Nicolas Savy, David A. A. Stephens, Erica E. M. Moodie, Marina B. B. Klein
Summary: Forecasting recruitments is crucial in the monitoring phase of multicenter studies. The Poisson-Gamma recruitment model is a popular technique based on the doubly stochastic Poisson process. However, the assumption of constant recruitment rates is often unrealistic in real studies. This paper presents a flexible generalization of the model, allowing varying enrollment rates over time using B-splines. The approach is shown to be suitable for a wide range of recruitment behaviors in simulations and is applied to estimate recruitment progression in a Canadian Co-infection Cohort.
STATISTICS IN MEDICINE
(2023)
Article
Physics, Multidisciplinary
Jaemin Lee, Juhuhn Kim, Hyunho Kim, Jong-Seok Lee
Summary: This study confirms the impact of the COVID-19 pandemic on football match results in four major European football leagues through statistical analysis. It proposes a Bayesian hierarchical Poisson model to estimate the parameters reflecting the home advantage. By including these parameters as additional features, the performance of football match prediction models is improved.
Article
Physics, Applied
Robert D. McMichael, Sean M. Blakley
Summary: This paper introduces computational methods and simplified algorithms that accelerate utility calculations, eliminating the barrier of utility calculation for practical application of efficient adaptive measurement.
PHYSICAL REVIEW APPLIED
(2022)
Article
Biochemistry & Molecular Biology
Michele Abate, Raffaello Pellegrino, Angelo Di Iorio, Vincenzo Salini
Summary: The aim of this study was to evaluate the changes in vitamins, hormones, free radicals, and antioxidant substances during the season and their association with performance improvement after training. The results showed that athletes had better performance after training, but no significant relationships were found between vitamin and hormone levels and the performance improvement. However, there was an indirect relationship between oxidative stress and performance improvement.
Article
Psychology
Arthur Prat-Carrabin, Robert C. Wilson, Jonathan D. Cohen, Rava Azeredo da Silveira
Summary: Studies have shown that humans adapt their inference processes to the temporal structure in the statistics of stimuli, deviating away from optimality quantitatively. Despite behaving qualitatively in a Bayesian fashion, human responses are variable and influenced by the temporal statistics of stimuli. Human behavior is best described by sampling-based inference models, which involve a compressed approximation of the posterior represented through a modest set of random samples.
PSYCHOLOGICAL REVIEW
(2021)
Article
Medical Laboratory Technology
Edmund H. Wilkes
Summary: According to international standards, clinical laboratories need to verify assay performance before routine practice. This paper presents an open-source software for Bayesian analysis of verification data, aiming to make Bayesian analyses more accessible. The software allows evaluation of imprecision, trueness, method comparison, and diagnostic performance within a Bayesian framework.
CLINICAL CHEMISTRY AND LABORATORY MEDICINE
(2023)
Article
Biology
Gustavo Nicolas Paez, Juan Felipe Ceron, Santiago Cortes, Adolfo J. Quiroz, Jose Fernando Zea, Camila Franco, Erica Cruz, Gina Vargas, Carlos Castaneda
Summary: This work evaluates four different models for estimating the basic reproduction number of a disease in a model-agnostic manner. The models are compared based on their theoretical foundations and tested through eight impartial simulations. The advantages and flaws of each model are discussed from both theoretical and practical perspectives.
BULLETIN OF MATHEMATICAL BIOLOGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Barry S. Eggleston, Joseph G. Ibrahim, Becky McNeil, Diane Catellier
Summary: BayesCTDesign is an R package for two-arm randomized Bayesian trial design. It allows users to incorporate historical control data and conduct simple two-arm randomized Bayesian trial design. The package offers simulation functions and methods for studying trial characteristics and estimating the power of hypothesis tests.
JOURNAL OF STATISTICAL SOFTWARE
(2021)
Article
Hospitality, Leisure, Sport & Tourism
Giuliano Bianchi, Cindy Yoonjoung Heo
Summary: Bayesian statistics approach introduces experts' opinions in quantitative analysis, particularly suitable for resolving the issue of observation shortage and handling subjective or abstract variables in the hospitality industry. Its potential importance in hospitality management research lies in its unique ability to incorporate expert opinions and tackle specific challenges in the field.
CURRENT ISSUES IN TOURISM
(2021)
Article
Instruments & Instrumentation
Peng Xu, Chen Fu, Jin-Jun Li, Lu Dong, Shan-Peng Zhao
Summary: This paper examines the estimation of parameters of radioactive point sources in a designated space using measurements collected by a plastic scintillator detector array, employing Bayesian estimation method and sequential Monte Carlo (SMC) method. Simulation analysis demonstrates that the Bayesian method accurately estimates the parameters of radioactive sources with measured background and source intensity data. Factors influencing the accuracy of estimation were investigated.
NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT
(2021)
Article
Operations Research & Management Science
Raffaele Mattera
Summary: This paper proposes a simple framework based on score-driven models to accurately predict binary outcomes in football matches. Two experiments are conducted to demonstrate the usefulness of this statistical approach.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Orthopedics
Tim Meyer, Vera Demond, Juergen Scharhag
Summary: German professional football coaches experience significant cardiocirculatory stress during matches, but do not show any match-induced cardiac damage, possibly due to their above-average fitness level.
CLINICAL JOURNAL OF SPORT MEDICINE
(2022)