Variational Inference for Intractable and Misspecified State Space Models

棘手且错误指定的状态空间模型的变分推理

• 批准号: DE230100029
• 负责人: Dr Ruben Loaiza-Maya
• 金额: $ 24.34万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE230100029
• 关键词: Variational; Inference; Intractable; Misspecified; State

State space models (SSMs) are popularly used to model economic variables such as inflation and financial volatility. Variational inference is a technique that allows for fast implementation of SSMs, but whose properties are yet to be understood. This project aims to study the properties of variational inference for SSMs used in economics. This research will develop new variational inference techniques to improve inferential and predictive accuracy from SSMs. An expected implication of this project is that it will expand the ability of economic institutions to employ larger SSMs, which will allow for more accurate models for economic variables. This will provide significant social benefits by leading to better informed economic policy.

状态空间模型（ssm）被广泛用于模拟经济变量，如通货膨胀和金融波动。变分推理是一种允许快速实现ssm的技术，但其特性尚未被理解。本项目旨在研究用于经济学的ssm的变分推理的性质。