Abstract
We investigate ordinary least‐squares and Bayesian methods for constructing interval estimates for historical lake pH's inferred from diatom sediments. The Bayesian method explicitly models several forms of variability, including the sampling and classification variability of the diatom records, estimation variability, and measurement error in observed pH's. The two methods produce similar interval estimates, but the Bayesian model allows design recommendations to be made.
Original language | English (US) |
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Pages (from-to) | 51-60 |
Number of pages | 10 |
Journal | Canadian Journal of Statistics |
Volume | 16 |
Issue number | 1 |
DOIs | |
State | Published - Mar 1988 |
Externally published | Yes |
Keywords
- Bayesian modelling
- acid deposition