The DOI matches its Crossref record, with a small difference in title or year; the references it cites are not checked yet.
Decision-Theoretic Foundations
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Under the Bayesian paradigm, nonidentifiability does not necessarily preclude inference and estimation, because informative prior distributions can identify the parameters nonetheless.
“When analyses are conducted under the Bayesian statistical paradigm, nonidentifiability does not necessarily preclude inference and estimation, because informative prior distributions can identify the parameters nonetheless [102, 103].”
From Integrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation (2015) · cites this paper as [103]
Citations
The citation lists haven’t been fetched yet
Cited by 1
Metadata
- Authors
- Robert, C. P.
- Affiliations
- Centre de Recherche en Mathématiques de la Décision (FR)
- Corresponding author
- Robert, Christian P.
- ORCID
- Robert, Christian P.
- Venue
- Springer Texts in Statistics
- Publisher
- Springer New York
- Published
- 2007-05-18
- Pages
- 51-103
- OpenAlex
- W142708206
- Cited by
- 1
- References
- 0
- Citations by year
- 2021: 1
- FWCI
- 0.00
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Keywords
- decision theory, statistical decision making, loss functions, risk minimization
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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