Computational modelling is a powerful tool for uncovering hidden processes in observed data, yet it faces underappreciated challenges. Among these, determining appropriate sample sizes for ...
In this paper, we introduce a novel model selection approach to time series forecasting. For linear stationary processes, such as AR processes, the direction of time is independent of the model ...
Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...
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