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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6 Pith papers cite this work. Polarity classification is still indexing.
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The sharp MSE bound for the ℓ1-minimum-norm interpolator under isotropic Gaussian covariates is recovered via the geometry of symmetric Gaussian polytopes, without the convex Gaussian min-max theorem.
A conditional Bayesian latent variable model with tailored Gibbs sampling improves variable selection and efficiency when relating ordinal academic performance to continuous self-efficacy.
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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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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Minimum Norm Interpolation via The Local Theory of Banach Spaces: The Role of Gaussianity
The sharp MSE bound for the ℓ1-minimum-norm interpolator under isotropic Gaussian covariates is recovered via the geometry of symmetric Gaussian polytopes, without the convex Gaussian min-max theorem.
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How does academic performance affect self-efficacy? Interpretable modelling through latent academic achievement
A conditional Bayesian latent variable model with tailored Gibbs sampling improves variable selection and efficiency when relating ordinal academic performance to continuous self-efficacy.
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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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