Abstract
Morris and Ebey reported the following curiosity. “The unweighted sample mean is examined as an estimator of the population mean in a first-order autoregressive model. It is demonstrated that the precision of this estimator deteriorates as the number of equally spaced observations taken within a fixed time interval increases.” Morris and Ebey proved their result but gave no intuition for it. We provide some intuition, then examine an implication: that the usual practice of estimating posterior expectations by taking the unweighted average of consecutive Markov chain Monte Carlo (MCMC) samples may not be optimal.
Original language | English (US) |
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Pages (from-to) | 1-6 |
Number of pages | 6 |
Journal | American Statistician |
Volume | 75 |
Issue number | 1 |
DOIs | |
State | Published - Feb 19 2019 |
Bibliographical note
Publisher Copyright:© 2019 The Author(s).
Keywords
- AR(1)
- Bayesian statistics
- MCMC
- Subsampling
- Weighted average