A Comparison of Methods for Computing Autocorrelation Time
Madeleine B. Thompson
TL;DR
This paper compares four methods for estimating autocorrelation time, finding that autoregressive process fitting is the most accurate, and provides an R package for further evaluation.
Contribution
It introduces a comparative analysis of autocorrelation time estimation methods and offers an R package for extending the evaluation.
Findings
Autoregressive process fitting is the most accurate method.
Four methods are evaluated on seven test series.
An R package is provided for further comparison.
Abstract
This paper describes four methods for estimating autocorrelation time and evaluates these methods with a test set of seven series. Fitting an autoregressive process appears to be the most accurate method of the four. An R package is provided for extending the comparison to more methods and test series.
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Taxonomy
TopicsStatistical Methods and Bayesian Inference · Statistical Methods and Inference · Advanced Statistical Methods and Models