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State Space Model/Evidence
Method evidence record

State Space Model

A state space model is a general time series framework that describes a series through unobserved (latent) state variables linked by a measurement equation and a transition equation, with the states estimated in real time by the Kalman filter. Developed in the state space tradition of Harvey (1990) and Durbin & Koopman (2012), it nests ARIMA and exponential smoothing as special cases.

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Source record

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

State Space Model (Kalman Filter)
Taxonomic method record · regression-model / econometrics
  • Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. · DOI 10.1017/CBO9781107049994
  • Durbin, J. & Koopman, S. J. (2012). Time Series Analysis by State Space Methods (2nd ed.). Oxford University Press. · DOI 10.1093/acprof:oso/9780199641178.001.0001
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Curated claims

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Related methods

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

Same method familyARIMAmachine-suggested · Relational suggestion, not evidence.Same method familyBayesian VARmachine-suggested · Relational suggestion, not evidence.Same method familyMarkov-Switching Modelmachine-suggested · Relational suggestion, not evidence.Same method familyStructural Time Series 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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