The DOI matches its Crossref record.
Parameter estimation in X-ray astronomy
Abstract
Two important problems encountered in X-ray astronomy are considered: the assessment of the validity of models, and the determination of values of adjustable parameters which valid models possess. Minimization of the chi-squared statistic is recommended for testing the validity of classes of models. The chi-squared min + 1 error estimation method is evaluated and found to be unsuitable when several parameter ranges are to be derived. The ratio of variances method gives parameter confidence regions which are more variable than necessary.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Statistics, Handle with Care: Detecting Multiple Model Components with the Likelihood Ratio Test
Protassov, R., van Dyk, D. A., Connors, A., Kashyap, V. L., & Siemiginowska, A. (2002) · The Astrophysical Journal · doi:10.1086/339856 · Cited by 678
Position measurement with a resolution and noise-limited instrument
Bobroff, N. (1986) · Review of Scientific Instruments · doi:10.1063/1.1138619 · Cited by 375
PRECISION MEASURES OF THE PRIMORDIAL ABUNDANCE OF DEUTERIUM
Cooke, R. J., Pettini, M., Jorgenson, R. A., Murphy, M. T., & Steidel, C. C. (2014) · The Astrophysical Journal · doi:10.1088/0004-637x/781/1/31 · Cited by 344
Swift Observations of GRB 070110: An Extraordinary X‐Ray Afterglow Powered by the Central Engine
Troja, E., Cusumano, G., O’Brien, P. T., Zhang, B., Sbarufatti, B., Mangano, V., Willingale, R., Chincarini, G., Osborne, J. P., Marshall, F. E., et al. (2007) · The Astrophysical Journal · doi:10.1086/519450 · Cited by 305
From Laplace to Supernova SN 1987A: Bayesian Inference in Astrophysics
Loredo, T. J. (1990) · Maximum Entropy and Bayesian Methods · doi:10.1007/978-94-009-0683-9_6 · Cited by 168
Metadata
- Authors
- Lampton, M., Margon, B., & Bowyer, S.
- Venue
- The Astrophysical Journal
- Publisher
- American Astronomical Society
- Published
- 1976-08
- Volume
- 208
- Pages
- 177
- ISSN
- 0004-637X (ISSN-L)
- 1538-4357
- OpenAlex
- W1977503055
- Cited by
- 690
- References
- 0
- FWCI
- 3.13
- Type
- journal article
- Language
- en
- Open access
- closed
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Parameter estimation in X-ray astronomy. https://app.cochat.ai/papers/10.1086/154592
- The paper
- Lampton, M., Margon, B., & Bowyer, S. (1976). Parameter estimation in X-ray astronomy. The Astrophysical Journal. https://doi.org/10.1086/154592
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
