The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Extracting distribution parameters from multiple uncertain observations with selection biases
Open accessAbstract
We derive a Bayesian framework for incorporating selection effects into population analyses. We allow for both measurement uncertainty in individual measurements and, crucially, for selection biases on the population of measurements, and show how to extract the parameters of the underlying distribution based on a set of observations sampled from this distribution. We illustrate the performance of this framework with an example from gravitational-wave astrophysics, demonstrating that the mass ratio distribution of merging compact-object binaries can be extracted from Malmquist-biased observations with substantial measurement uncertainty.
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Cites
Stan : A Probabilistic Programming Language
Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M., Guo, J., Li, P., & Riddell, A. (2017) · Journal of Statistical Software · doi:10.18637/jss.v076.i01 · Cited by 7,754 · cited 1×
“Code and results implementing this model in the stan sampler (Carpenter et al. 2017) can be found at https://github.com/farr/SelectionExample.”
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Cited by
Abbott, B. P., Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., et al. (2019) · The Astrophysical Journal Letters · doi:10.3847/2041-8213/ab3800 · Cited by 895
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Metadata
- Authors
- Mandel, I., Farr, W. M., & Gair, J. R.
- Venue
- Monthly Notices of the Royal Astronomical Society
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-03-28
- Volume
- 486
- Issue
- 1
- Pages
- 1086-1093
- ISSN
- 0035-8711 (ISSN-L)
- 1365-2966
- OpenAlex
- W2891993472
- Cited by
- 413
- References
- 1
- FWCI
- 24.34
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Extracting distribution parameters from multiple uncertain observations with selection biases. https://app.cochat.ai/papers/10.1093/mnras/stz896
- The paper
- Mandel, I., Farr, W. M., & Gair, J. R. (2019). Extracting distribution parameters from multiple uncertain observations with selection biases. Monthly Notices of the Royal Astronomical Society. https://doi.org/10.1093/mnras/stz896
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
