UCLA

The first part of the dissertation focusses on spatial and temporal modeling of point processes on linear networks. Point processes on/near linear networks can simply be defined as point events occurring on or near line segment network structures embedded in a certain space. A separable modeling framework is presented that fits a formation and a dissolution model of point processes on linear networks over time. Two major applications of the separable temporal model are spider web building activity in brick mortar lines and wildfire ignition origins near road networks.

The second part of the dissertation focusses on analyses of large energy databases, specifically the Energy Atlas database. The main motivation of this part is to explore and understand the issues of balancing necessary data resolution while maintaining consumer privacy.

The issue of data resolution and its importance are explored by first tackling a specific policy objective. This is achieved by applying a longitudinal quantile regression model to parcel-level monthly energy consumption in the Westwood neighborhood; the model results aid in fulfilling efficiency goals outlined in the California Senate Bill 350. Then the issue of record privacy is explored through a review of current privacy methods, implementation, data ownership, and concluded with avenues of future research.