The authors introduce Time to Transition (TtT) extracted from cross-maturity greenium differences and develop tractable deadline-constrained and regime-switching diffusion models with exact likelihoods and asymptotic identification results for inference.
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Embedding selection mechanisms into generative simulators enables amortized Bayesian inference to produce debiased, well-calibrated posteriors without tractable likelihoods.
A computationally efficient three-step marginal method for longitudinal function-on-function regression that fits pointwise scalar-on-function models, smooths along the bivariate domain, and derives confidence bands to enable valid inference on large functional datasets.
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Overcoming Selection Bias in Statistical Studies With Amortized Bayesian Inference
Embedding selection mechanisms into generative simulators enables amortized Bayesian inference to produce debiased, well-calibrated posteriors without tractable likelihoods.