A network flow approach in finding maximum likelihood estimate of high concentration regions

DOI10.1016/S0167-9473(03)00134-8zbMath1429.62429MaRDI QIDQ956897

Xiaoming Huo, Jye-Chyi Lu

Publication date: 26 November 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

zbMATH Keywords

point processesenvelopehigh activity regionshigh concentration regionhigh density region

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Inference from spatial processes (62M30) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (3)

A data-adaptive method for estimating density level sets under shape conditions ⋮ Asymptotic normality of plug-in level set estimates ⋮ A comparative simulation study of data-driven methods for estimating density level sets

Cites Work

• Estimation of the envelope of a point set with loose boundaries
• Detecting Features in Spatial Point Processes with Clutter via Model-Based Clustering
• Nearest-Neighbor Clutter Removal for Estimating Features in Spatial Point Processes
• Nonparametric Maximum Likelihood Estimation of Features in Spatial Point Processes Using Voronoi Tessellation
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