Resampling Inhomogeneous Marked Point Processes

• Activity Number: 373
• Type: Contributed
• Date/Time: Tuesday, August 11, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Business and Economic Statistics Section
• Author(s): William Garner* and Dimitris Politis
• Companies: Gilead Sciences and UC San Diego
• Keywords: resampling ; local block bootstrap ; inhomogeneous ; poisson

Abstract

We investigate methods for resampling inhomogeneous marked point processes, focusing on Poisson point processes. First, we introduce the problem and provide some background information. Then we adapt existing methods for resampling homogeneous marked point processes to the case of one-dimensional inhomogeneous marked point processes data. Next, we extend theoretical results such as asymptotic normality from the homogeneous to the inhomogeneous setting. We continue by establishing the validity of our local block bootstrap procedure for one-dimensional inhomogeneous marked point processes data and finish by comparing the performance of the various one-dimensional methods.