ABC Shadow algorithm: a tool for statistical analysis of spatial patterns

作者：Stoica Radu S^*; Philippe Anne; Gregori Pablo; Mateu Jorge

来源：Statistics and Computing, 2017, 27(5): 1225-1238.

DOI：10.1007/s11222-016-9682-x

• Approximate Bayesian computation
• Computational methods in Markov chains
• Maximum likelihood estimation
• Point processes
• Spatial pattern analysis

This paper presents an original ABC algorithm, ABC Shadow, that can be applied to sample posterior densities that are continuously differentiable. The proposed algorithm solves the main condition to be fulfilled by any ABC algorithm, in order to be useful in practice. This condition requires enough samples in the parameter space region, induced by the observed statistics. The algorithm is tuned on the posterior of a Gaussian model which is entirely known, and then, it is applied for the statistical analysis of several spatial patterns. These patterns are issued or assumed to be outcomes of point processes. The considered models are: Strauss, Candy and area-interaction.

• 出版日期2017-9
• 单位INRIA