应用统计
In recent years, and particularly during the Covid-19 pandemic, Morocco has experienced significant pressure from user demand, leading to a significant workload in public hospitals. This situation raises major questions regarding the…
Using data collected on almost every 9-12 years old student in Uruguay, we show how to apply Bayesian Additive Regression Trees (BART) with random effects to study performance association with Learning Managment System (LMS) activity and…
Introduction Lifetime risks quantify health risks from radiation exposure and play an important role in radiation detriment and radon dose conversion. This study considers the lifetime risk of dying from lung cancer related to occupational…
Predicting the results of soccer matches is of great interest. This is not only due to the popularity of the sport and the joy of private "betting rounds", but also due to the large sports betting market. Where previously expert knowledge…
We propose a novel framework for modeling the yield curve from a quantile perspective. Building on the dynamic Nelson-Siegel model of Diebold et al. (2006), we extend its traditional mean-based approach to a quantile regression setting,…
Air and water pollution are major threats to public health, highlighting the need for reliable environmental monitoring. Low-cost multisensor systems are promising but suffer from limited selectivity, because their responses are influenced…
The gut microbiome plays a crucial role in human health, making it a corner stone of modern biomedical research. To study its structure and dynamics, machine learning models are increasingly used to identify key microbial patterns…
The Brier score is a widely used metric evaluating overall performance of probabilistic predictions for binary outcomes in clinical research. However, its interpretation can be complex, as it does not align with commonly taught concepts in…
Short-term shifts in booking behaviors can disrupt forecasting in the travel and hospitality industry, especially during global crises. Traditional metrics like average or median lead times often overlook important distribution changes.…
Assessing forecasting performance is a time intensive activity, often requiring months or years before we know whether or not the reported forecasts were accurate. Cognitive tests can be quickly administered and are predictive of…
Pregnancy loss is recognized as an important competing event in studies of prenatal medication use. However, a healthy live birth also precludes subsequent adverse pregnancy outcomes, yet these events are often censored. Using Monte Carlo…
Background. Radiomic features, derived from a region of interest (ROI) in medical images, are valuable as prognostic factors. Selecting an appropriate ROI is critical, and many recent studies have focused on leveraging multiple ROIs by…
This study presents a comprehensive assessment of the Italian risk model used during the COVID-19 pandemic to guide regional mobility restrictions through a colour-coded classification system. The research focuses on evaluating the…
Bayesian adaptive clinical trials offer a flexible and efficient alternative to traditional fixed-design trials, but their implementation is often hindered by the complexity of Bayesian computations and the need for advanced statistical…
Regressions are commonly used in environmental science and economics to identify causal or associative relationships between variables. In these settings, remote sensing-derived map products increasingly serve as sources of variables,…
Reanalysis products such as the ERA5 reanalysis are commonly used as proxies for observed atmospheric conditions. These products are convenient to use due to their global coverage, the large number of available atmospheric variables and the…
Annual maximum temperature data provides crucial insights into the impacts of climate change, especially for regions like India, where temperature variations have significant implications for agriculture, health, and infrastructure. In this…
In 2024, Major League Baseball released new bat tracking data, reporting swing-by-swing bat speed and swing length measured at the point of contact. While exciting, the data present challenges for their interpretation. The timing of the…
The Drift-Diffusion Model (DDM) is widely used in neuropsychological studies to understand the decision process by incorporating both reaction times and subjects' responses. Various models have been developed to estimate DDM parameters,…
Kaplan-Meier estimate, commonly known as product limit method (PLM), and maximum likelihood estimate (MLE) methods in general are often cited as means of stochastic highway capacity estimation. This article discusses their unsuitability for…