Simulations play important and diverse roles in statistical workflows, for example, in model specification, checking, validation and even directly in model inference. Over the past decades, the application areas and overall potential of simulations in statistical workflows have expanded significantly, driven by the development of new simulation-based algorithms and exponentially increasing computational resources. In this paper, we examine past and current trends in the field and offer perspectives on how simulations may shape the future of statistical practice. This article is part of the theme issue 'Statistical workflow'.
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