Over the past years, machine learning emerged as a powerful tool for credit scoring, producing high-quality results compared to traditional statistical methods. However, literature shows that statistical methods are still being used because they still perform and can be interpretable compared to...

Nonlinear regression models are extensively applied across various scientific disciplines. It is vital to accurately fit the optimal nonlinear model while considering the biases of the Bayesian optimal design. We present a Bayesian optimal design by utilising the Dirichlet process as a prior....

Karpowitz et al. (2024) examine the effect of racial diversity on group decisionmaking. The authors used OLS regression to analyze 2,694 citizens randomly assigned to 449 mock juries who are tasked to make decisions, and they find that the number of the people of color (POC) affects private...

Understanding how corruption affects the relationship between natural resources and growth has profound implications for sustainable development goals in Sub-Saharan Africa (SSA). This study investigates the nexus between natural resources, economic growth, and corruption in SSA from 1985 to...

We offer a simple analysis of the problem of choosing a statistical experiment to optimize the induced distribution of posterior medians or, more generally, q-quantiles for any q ∈ (0,1). We show that a single experiment-the q-quantile matching experiment-implements all implementable...