Abstract. This paper introduces a novel multivariate composite estimator for the Labour Force Survey (LFS). The estimator improves upon traditional methods

Abstract. It is increasingly common to study mobility and migration of individuals between social and physical locations as networks in which locations are

Abstract. Analysing crime events is crucial to understand crime dynamics, and it is largely helpful for constructing prevention policies. Point processes s

Abstract. The paper introduces a novel framework for small area estimation based on spatio-temporal M-quantile regression. The proposed approach extends th

Abstract. Signed networks capture the polarity of relationships between nodes, providing valuable insights into complex systems where both supportive and a

Abstract. Understanding how relationships among global financial markets change over time is crucial for effective risk management, portfolio diversificati

Abstract. The paper develops a dynamic panel stochastic frontier model that incorporates firms’ intertemporal decision behaviour and short-run stagnant adj

Abstract. In meta-analysis, the conventional random-effects model (REM) is commonly used when heterogeneity is thought probable a priori. However, there ar

Abstract. This article leverages Wasserstein Propagation in Social Network to propose a novel distributional framework for the inference of cyber risk acro

Abstract. Polygenic hazard scores (PHS) designed for European ancestry (EUR) individuals provide ample information regarding risk discrimination. Incorpora

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Abstract. The acute phase of the COVID-19 pandemic has made apparent the need for decision support based upon accurate epidemic modelling. This process is

Abstract. Player tracking data have provided great opportunities to generate insights into understudied areas of American football, such as pre-snap motion

Abstract. We propose a multi-state quantile regression model that admits a cure-fraction for each possible transition, so that individuals may not experien