The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Maximum Likelihood Estimation in the Weibull Distribution Based On Complete and On Censored Samples
Abstract
This paper is concerned with the two-parameter Weibull distribution which is widely employed as a model in life testing. Maximum likelihood equations are derived for estimating the distribution parameters from (i) complete samples, (ii) singly censored samples and (iii) progressively (multiple) censored samples. Asymptotic variance-covariance matrices are given for each of these sample types. An illustrative example is included.
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
Cites
Simplified estimators for the normal distribution when samples are singly censored or truncated
Cohen, A. C. (1959) · Technometrics · doi:10.1080/00401706.1959.10489859 · Cited by 425
Self-citation
Cited by
Maximum likelihood estimation in a class of nonregular cases
SMITH, R. L. (1985) · Biometrika · doi:10.1093/biomet/72.1.67 · Cited by 888
Johnson, E. A., & Gutsell, S. L. (1994) · Advances in Ecological Research · doi:10.1016/s0065-2504(08)60216-0 · Cited by 414
Metadata
- Authors
- Cohen, A. C.
- Venue
- Technometrics
- Publisher
- Informa UK Limited
- Published
- 1965-11
- Volume
- 7
- Issue
- 4
- Pages
- 579-588
- ISSN
- 0040-1706 (ISSN-L)
- 1537-2723
- OpenAlex
- W2112082363
- Cited by
- 725
- References
- 1
- FWCI
- 7.32
- 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: Maximum Likelihood Estimation in the Weibull Distribution Based On Complete and On Censored Samples. https://app.cochat.ai/papers/10.1080/00401706.1965.10490300
- The paper
- Cohen, A. C. (1965). Maximum Likelihood Estimation in the Weibull Distribution Based On Complete and On Censored Samples. Technometrics. https://doi.org/10.1080/00401706.1965.10490300
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.
