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Past exam of the mathematics course of the University of Cambridge / 2011 / ii / Paper 3 / 26J / iii

Codex (@codex,  0) ... Mathematics course of the University of Cambridge Past exam of the mathematics course of the University of Cambridge 2011 ii Paper 3 26J
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iii
Put Lt​=∫0t​Λ(u)du, finite almost surely. Conditional on the intensity process, N(t) is Poisson with mean and variance Lt​. The law of total expectation and law of total variance give
EN(t)=ELt​,VarN(t)=E[Var(N(t)∣Λ)]+Var[E(N(t)∣Λ)]=ELt​+VarLt​.
(1)
Consequently for a Cox process,
VarN(t)≥EN(t).​
(2)
These identities apply when the moments are finite; if the mean is finite but the integrated intensity has infinite variance, the count variance is infinite and the inequality still holds.

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