New splitting-scheme-based pseudo-likelihood estimators for SDEs with Hölder multiplicative noise that achieve strong convergence, state-space preservation, consistency, and asymptotic normality.
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The statistical method used to predict AMOC collapse timing from historical sea-surface temperatures is highly sensitive to unaccounted uncertainties and does not reliably constrain the collapse time.
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Splitting schemes and estimators for stochastic differential equations with H\"older multiplicative noise
New splitting-scheme-based pseudo-likelihood estimators for SDEs with Hölder multiplicative noise that achieve strong convergence, state-space preservation, consistency, and asymptotic normality.
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Extrapolation from historical data cannot reliably predict the time of a potential AMOC collapse
The statistical method used to predict AMOC collapse timing from historical sea-surface temperatures is highly sensitive to unaccounted uncertainties and does not reliably constrain the collapse time.