A new data-synthesized instrumental variable estimator achieves finite-sample Lp consistency with sqrt(n) rate for linear-in-parameters models in discrete and continuous time, cutting bias by hundreds of times on Lorenz examples.
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A hybrid iterative-sequential method identifies linear DAE systems from errors-in-variables data by partial lagged-data stacking and iterative diagonal error-covariance estimation.
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Instrumental variables system identification with $L^p$ consistency
A new data-synthesized instrumental variable estimator achieves finite-sample Lp consistency with sqrt(n) rate for linear-in-parameters models in discrete and continuous time, cutting bias by hundreds of times on Lorenz examples.