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A.11 Proof of Proposition 8

As shown before, if $g(\theta_i, e_i) = \theta_i e_i$, we have

(ddeigek1(gei(ti+x)))e1==en=e=(ti+x)e. \left. \left( \frac{d}{de_i} g_{e_k}^{-1} (g_{e_i}(t_i + x)) \right) \right|_{e_1=\dots=e_n=e} = \frac{(t_i+x)}{e}.

Thus, making use of expression (11), derived in Section B.1, and denoting $\Delta t = t_1 - t > 0$,

λ2Δt(H(x)kiH(Δt+x))(ki(ddeigek1(gei(t1+x))))e1==en=edx=λ2Δtexp(nλy)exp((n1)λ(Δt+x))(n1)(t1+x)edx=λ2(n1)eΔtexp(nλy+(n1)λΔt)(t1+y)dy. \begin{align*} & \lambda^2 \int^{-\Delta t} \left( H(x) \prod_{k \neq i} H(\Delta t + x) \right) \left( \sum_{k \neq i} \left( \frac{d}{de_i} g_{e_k}^{-1} (g_{e_i}(t_1+x)) \right) \right) \Big|_{e_1=\dots=e_n=e} dx \\ &= \lambda^2 \int^{-\Delta t} \exp(n\lambda y) \cdot \exp((n-1)\lambda(\Delta t + x)) (n-1) \frac{(t_1+x)}{e} dx \\ &= \frac{\lambda^2(n-1)}{e} \int^{-\Delta t} \exp(n\lambda y + (n-1)\lambda\Delta t)(t_1+y) dy. \end{align*}

The map $\phi_2 : \mathbb{R}_x \to \mathbb{R}_y$ given by $x \to y = -\Delta t + x$ is a smooth diffeomorphism with $\det|\phi_2'(x)| = 1$. Applying the associated change of variables to the integral, we obtain

λ2(n1)e0exp(nλ(xΔt)+(n1)λΔt)(t+x)dx=(n1)eexp(λΔt)λ2(0xexp(nλx)dx+t0exp(nλx)dx). \begin{align*} & \frac{\lambda^2(n-1)}{e} \int^0 \exp(n\lambda(x-\Delta t) + (n-1)\lambda\Delta t)(t+x)dx \\ &= \frac{(n-1)}{e} \exp(-\lambda\Delta t) \lambda^2 \left( \int^0 x \exp(n\lambda x)dx + t \int^0 \exp(n\lambda x)dx \right). \end{align*}

Notice that

nλ0xexp(nλx)dx n\lambda \int^{0} x \exp(n\lambda x) dx

is the mean of a random variable that is distributed according to the reflected exponential distribution with parameter $n\lambda$, hence

nλ0xexp(nλx)dx=1nλ n\lambda \int^{0} x \exp(n\lambda x) dx = -\frac{1}{n\lambda}

0xexp(nλx)dx=1n2λ2. \Leftrightarrow \int^{0} x \exp(n\lambda x) dx = -\frac{1}{n^2\lambda^2}.

Furthermore,

nλ0exp(nλx)dx=1 n\lambda \int^{0} \exp(n\lambda x) dx = 1

0exp(nλx)dx=1nλ. \Leftrightarrow \int^{0} \exp(n\lambda x) dx = \frac{1}{n\lambda}.