Combining datasets for Bayesian inference Article Swipe
Bayesian inference (BI) has long been used to estimate posterior parameter distributions based on multiple sets of data. Here, we present elementary derivations of two strategies for doing so. The first approach employs the posterior distribution from a BI calculation on one dataset as the prior distribution for a second dataset. The second approach uses importance sampling, augmenting the posterior from one dataset to form a well-targeted sampling function for the second. In both cases, the distribution sampled is shown to be the ``full posterior'' as if BI were performed on the two datasets together, subject to only mild assumptions. Both methods can be applied in sequence to multiple datasets.
Related Topics
Concepts
Posterior probability
Inference
Bayesian probability
Bayesian inference
Computer science
Posterior predictive distribution
Sampling (signal processing)
Categorical distribution
Prior probability
Bayesian hierarchical modeling
Artificial intelligence
Sampling distribution
Bayesian linear regression
Pattern recognition (psychology)
Data mining
Mathematics
Statistics
Filter (signal processing)
Computer vision
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.31219/osf.io/hv7yd
- https://osf.io/hv7yd/download
- OA Status
- gold
- Cited By
- 3
- References
- 4
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388773345
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4388773345Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.31219/osf.io/hv7ydDigital Object Identifier
- Title
-
Combining datasets for Bayesian inferenceWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-11-16Full publication date if available
- Authors
-
Daniel M. ZuckermanList of authors in order
- Landing page
-
https://doi.org/10.31219/osf.io/hv7ydPublisher landing page
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-
https://osf.io/hv7yd/downloadDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://osf.io/hv7yd/downloadDirect OA link when available
- Concepts
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Posterior probability, Inference, Bayesian probability, Bayesian inference, Computer science, Posterior predictive distribution, Sampling (signal processing), Categorical distribution, Prior probability, Bayesian hierarchical modeling, Artificial intelligence, Sampling distribution, Bayesian linear regression, Pattern recognition (psychology), Data mining, Mathematics, Statistics, Filter (signal processing), Computer visionTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
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2025: 1, 2024: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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