presents a multivariate probabilistic forecasting model that addresses the challenges posed by imbalanced data resulting from … Variogram-based Scores. These improvements underscore the importance of addressing imbalanced data and utilizing multivariate …

This paper introduces a novel multivariate composite estimator for the Labour Force Survey (LFS). Unlike the univariate … composite estimators used in some countries, the multivariate estimator takes into account the different probabilities of … between the total population and the sum of others. The multivariate approach improves the accuracy of the population …

In the analysis of multivariate stochastic volatility models, many estimation procedures begin by transforming the data …

-dimensional multivariate models it is computationally cumbersome as estimation requires the evaluation of multivariate normal distribution …), circumvents this multivariate integration problem. The method is based on the assumed zero correlations between explanatory … multivariate normal. It can be implemented by repeated application of standard techniques. GMM provides a simpler and faster …

two-stage inference method using the Sarmanov family of multivariate distributions to the actuarial literature. In fact … and a better diversification benefit. We extend the model to the multivariate case with more than two lines of business …