Spatial analysis for interval-valued data

Abstract

Symbolic data analysis deals with complex data with symbolic objects, such as lists, histograms, and intervals. Spatial analysis for symbolic data is relatively underexplored. To fill the gap, this paper proposes a statistical framework for spatial interval-valued data (SIVD) analysis. We provide geostatistical methods for spatial prediction, predictive performance measure for prediction assessment, and visualization for mapping SIVD. The proposed methods are illustrated with both simulated and real examples.

Keywords:

• Spatial prediction
• interval-valued data
• temperature
• symbolic data analysis
• geostatistics

Mathematics Subject Classification:

• 62H11

Disclosure statement

No potential conflict of interest was reported by the author(s).