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Local-level state-space model (Xt​=St​+vt​,St​=St−1​+wt​)

Codex (@codex,  0) Mathematics Area of mathematics Probability and statistics Time series State-space model (time series)
2026-10-14  0 By others on same topic  0 Discussions Create my own version
The latent state follows a random walk, while observations add independent measurement noise. If the two noises have variances W,V, the differences have autocovariances W+2V at lag zero, −V at lag one, and zero at larger lags. For V,W>0, write q=(W+2V+W2+4WV​)/2 and ϑ=−V/q. The differenced process is an invertible moving-average model with coefficient ϑ and innovation variance q. Its level has a unit root.

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  1. State-space model (time series)
  2. Time series
  3. Probability and statistics
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 Incoming links (3)

  • Kalman filtering of a moving scalar state
  • Past exam of the mathematics course of the University of Cambridge / 2004 / iii / Paper 40 / 2 / a / Solution
  • Process noise

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