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Time-varying parameter GLS/Evidence
Method evidence record

Time-varying parameter GLS

Time-varying parameter GLS extends generalized least squares to settings where regression coefficients are not fixed constants but evolve over time according to a stochastic process. By embedding the model in a state-space framework and applying GLS corrections for non-spherical errors, it captures structural change, regime shifts, and gradually drifting relationships in time-series data.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Time-Varying Parameter Generalized Least Squares
Taxonomic method record · regression-model / econometrics
  • Cooley, T. F., & Prescott, E. C. (1976). Estimation in the presence of stochastic parameter variation. Econometrica, 44(1), 167–184. · DOI 10.2307/1911389
  • Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. · ISBN 9780521321969
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Curated claims

Claims persisted in the evidence ledger, each with its own assessment.

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

See alsoKalman Filtermachine-suggested · Relational suggestion, not evidence.Same method familyState Space Modelmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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