The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Iteratively Reweighted Least Squares for Maximum Likelihood Estimation, and Some Robust and Resistant Alternatives
Abstract
SUMMARY: The scope of application of iteratively reweighted least squares to statistical estimation problems is considerably wider than is generally appreciated. It extends beyond the exponential-family-type generalized linear models to other distributions, to non-linear parameterizations, and to dependent observations. Various criteria for estimation other than maximum likelihood, including resistant alternatives, may be used. The algorithms are generally numerically stable, easily programmed without the aid of packages, and highly suited to interactive computation.
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
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
A Simplex Method for Function Minimization
Nelder, J. A., & Mead, R. (1965) · The Computer Journal · doi:10.1093/comjnl/7.4.308 · Cited by 28,905
(2005) · Statistics for Biology and Health · doi:10.1007/0-387-27255-0_9 · Cited by 20,133
David, F. N., & Tukey, J. W. (1977) · Biometrics · doi:10.2307/2529486 · Cited by 12,708
Linear Statistical Inference and its Applications: Second Editon
Rao, C. R. (1973) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316436 · Cited by 10,489
Nelder, J. A., & Wedderburn, R. W. M. (1972) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344614 · Cited by 7,194
Simple mathematical models with very complicated dynamics
May, R. M. (1976) · Nature · doi:10.1038/261459a0 · Cited by 7,001
Techniques for Testing the Constancy of Regression Relationships Over Time
Brown, R. L., Durbin, J., & Evans, J. M. (1975) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1975.tb01532.x · Cited by 5,128
Discrete Multivariate Analysis: Theory and Practice.
Beniger, J. R., Bishop, Y. M. M., Feinberg, S. E., Holland, P. W., Light, R. J., & Mosteller, F. (1975) · Contemporary Sociology · doi:10.2307/2063625 · Cited by 5,108
Function minimization by conjugate gradients
Fletcher, R. (1964) · The Computer Journal · doi:10.1093/comjnl/7.2.149 · Cited by 4,939
Cited by
Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
Lambert, D. (1992) · Technometrics · doi:10.2307/1269547 · Cited by 3,988
Improving predictive inference under covariate shift by weighting the log-likelihood function
Shimodaira, H. (2000) · Journal of Statistical Planning and Inference · doi:10.1016/s0378-3758(00)00115-4 · Cited by 1,678
Dataset Shift in Machine Learning
(2008) · doi:10.7551/mitpress/9780262170055.001.0001 · Cited by 1,553
Some aspects of the spline smoothing approach to non-parametric regression curve fitting
Silverman, B. W. (1985) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1985.tb01327.x · Cited by 1,117
Zero‐Inflated Poisson and Binomial Regression with Random Effects: A Case Study
Hall, D. B. (2000) · Biometrics · doi:10.1111/j.0006-341x.2000.01030.x · Cited by 913
Metadata
- Authors
- Green, P. J.
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 1984-01-01
- Volume
- 46
- Issue
- 2
- Pages
- 149-170
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W2903718010
- Cited by
- 687
- References
- 60
- FWCI
- 19.29
- 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: Iteratively Reweighted Least Squares for Maximum Likelihood Estimation, and Some Robust and Resistant Alternatives. https://app.cochat.ai/papers/10.1111/j.2517-6161.1984.tb01288.x
- The paper
- Green, P. J. (1984). Iteratively Reweighted Least Squares for Maximum Likelihood Estimation, and Some Robust and Resistant Alternatives. Journal of the Royal Statistical Society Series B: Statistical Methodology. https://doi.org/10.1111/j.2517-6161.1984.tb01288.x
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.
