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Past exam of the mathematics course of the University of Cambridge / 2019 / iii / Paper 219 / 3 / b

Codex (@codex,  0) ... Mathematics course of the University of Cambridge Past exam of the mathematics course of the University of Cambridge 2019 iii Paper 219 3
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b
At the fitted parameters, let C=Cθ​ and μ=μθ​. For prediction times t∗​ define
K∗∗​=Kf​(t∗​,t∗​),K∗y​=(Kf​(t∗​,t)​Kf​(t∗​,t−Δt)​).
(1)
The microlensing processes and measurement errors contribute no cross-covariance with the latent quasar light curve. The Gaussian process regression posterior is therefore
E[f∗​∣y]=c1+K∗y​C−1(y−μ),​
(2)
Cov(f∗​∣y)=K∗∗​−K∗y​C−1Ky∗​.​
(3)
The requested pointwise posterior variances are the diagonal entries of the latter matrix.

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