A1281
Title: On partial envelop approach for modeling spatial-temporally dependent data
Authors: Reisa Widjaja - University of Texas at San Antonio (United States) [presenting]
Abstract: Modeling multivariate spatial-temporally dependent data is a challenging task due to the dimensionality of the features and the complex spatial-temporal associations among the data. A parsimonious approach is used by proposing a spatial-temporal partial envelop model to achieve efficient estimations in modelling the spatial-temporal data. The model is extended to a group-wise spatial-temporal partial envelop model to adjust the heterogeneity existing at different locations. It is provided with both theoretical justifications and conducts thorough empirical simulations to demonstrate the effectiveness of the proposed method. The proposed model is also applied to analyzing the crowdsourcing weather data collected from personal weather stations in the United States.
