Sampling Errors in Nested Sampling Parameter Estimation

Abstract

Sampling errors in nested sampling parameter estimation differ from those in Bayesian evidence calculation, but have been little studied in the literature. This paper provides the first explanation of the two main sources of sampling errors in nested sampling parameter estimation, and presents a new diagrammatic representation for the process. We find no current method can accurately measure the parameter estimation errors of a single nested sampling run, and propose a method for doing so using a new algorithm for dividing nested sampling runs. We empirically verify our conclusions and the accuracy of our new method.

Very minor changes. 22 pages + appendix, 10 figures. Accepted by Bayesian Analysis

References in corpus (2)

• PolyChord: nested sampling for cosmology
• Markov Chain Monte Carlo: Can We Trust the Third Significant Figure?

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