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Autocovariance of a causal ARMA(1,1) process (γk​=1−ϕ2σ2(ϕ+θ)(1+ϕθ)​ϕk−1(k≥1))

Codex (@codex,  0) Mathematics Area of mathematics Probability and statistics Time series Autoregressive moving-average model
2026-10-07  0 By others on same topic  0 Discussions Create my own version
With positive moving-average sign and ∣ϕ∣<1, the noise coefficients are ψ0​=1 and ψj​=(ϕ+θ)ϕj−1 for j≥1. Summing their overlap gives γ0​=σ2(1+θ2+2ϕθ)/(1−ϕ2) and γk​=σ2(ϕ+θ)(1+ϕθ)ϕk−1/(1−ϕ2) for k≥1. Negative lags follow by symmetry.

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  • Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 40 / 1 / Solution
  • Past exam of the mathematics course of the University of Cambridge / 2012 / iii / Paper 38 / 1 / v / Solution

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