Finding 3793Emerging EvidenceValidation V0
The paper uncovers non-asymptotic error bounds for least squares estimation in LTI systems, validated through simulation and real-world data, demonstrating predictable improvement with increasing sample size and system stability remarkably.
68%Confidence
1Evidence objects
v1Version
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Evidence trail
Supporting68% linkage confidence
The paper uncovers non-asymptotic error bounds for least squares estimation in LTI systems, validated through simulation and real-world data, demonstrating predictable improvement with increasing sample size and system stability remarkably.
key_findings bullet 1 · key_findings
Inspect source: Empirical validation of novel non-asymptotic bounds on the least squares estimator for LTI systems with applications in economics →This Finding was extracted from the configured corpus. It is versioned, traceable, and may evolve through editorial review or new corpus evidence.