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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4 Pith papers cite this work. Polarity classification is still indexing.
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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.
Compares supervised architectures for political text scaling to evaluate joint prediction benefits and classification-regression middle grounds.
citing papers explorer
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Market-implied time to transition to a low-carbon economy: a stochastic modelling and inference framework
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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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.
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Efficient Longitudinal Function-on-Function Regression
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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Comparing Architectures for Supervised Political Scaling
Compares supervised architectures for political text scaling to evaluate joint prediction benefits and classification-regression middle grounds.