A dynamic factor model with jointly evolving level and volatility factors improves density forecast accuracy for international inflation, especially in tails and at medium horizons.
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Modifies Gibbs sampler for GP state-space models, introduces CFA measurement structure, and validates software via simulation-based calibration to enable reliable learning of nonlinear latent dynamics.
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A Dynamic Factor Model for Level and Volatility
A dynamic factor model with jointly evolving level and volatility factors improves density forecast accuracy for international inflation, especially in tails and at medium horizons.
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Learning Nonlinear Dynamics: Improving the Estimation Efficiency and Reliability of Gaussian Process State-Space Models
Modifies Gibbs sampler for GP state-space models, introduces CFA measurement structure, and validates software via simulation-based calibration to enable reliable learning of nonlinear latent dynamics.