  Tweedie exponential dispersion family constitutes a fairly rich sub-class of
the celebrated exponential family. In particular, a member, compound Poisson
gamma (CP-g) model has seen extensive use over the past decade for modeling
mixed response featuring exact zeros with a continuous response from a gamma
distribution. This paper proposes a framework to perform residual analysis on
CP-g double generalized linear models for spatial uncertainty quantification.
Approximations are introduced to proposed framework making the procedure
scalable, without compromise in accuracy of estimation and model complexity;
accompanied by sensitivity analysis to model mis-specification. Proposed
framework is applied to modeling spatial uncertainty in insurance loss costs
arising from automobile collision coverage. Scalability is demonstrated by
choosing sizable spatial reference domains comprised of groups of states within
the United States of America.
