Endpoint control for a Laplace-family conjugate posterior (source code)

= Endpoint control for a Laplace-family conjugate posterior

In the positive-support <exponential family> $q(\theta)=\int p(x)e^{-\theta x}\,dx$, a proper <natural conjugate prior> with zero endpoint density values has mean parameter strictly inside the essential convex support $(a,b)$. Updating that mean by a positive-weight average with supported observations keeps it inside $(a,b)$. At finite parameter endpoints, prior vanishing forces $q\to\infty$, so the increased posterior power $q^{-k-n}$ still vanishes. At positive infinity, positive base-measure mass below a point $d$ smaller than the updated mean bounds $q(\theta)$ below by $Ce^{-d\theta}$, giving <exponential decay> of the posterior kernel. Mass above the updated mean gives the analogous bound at negative infinity. Thus the updated density is proper and has the boundary condition required to integrate its score.