CoChat
Sign Up
Cited by 2,122Statistical Methods and Bayesian InferenceStatistical and numerical algorithmsStatistical Distribution Estimation and Applications

The DOI matches its Crossref record.

Quasi-Likelihood Functions, Generalized Linear Models, and the Gauss-Newton Method

Wedderburn, R. W. M.·1974·Biometrika
DOI 10.2307/2334725
Open this paper in CoChat — free account

Abstract

To define a likelihood we have to specify the form of distribution of the observations, but to define a quasi-likelihood function we need only specify a relation between the mean and variance of the observations and the quasi-likelihood can then be used for estimation. For a one-parameter exponential family the log likelihood is the same as the quasi-likelihood and it follows that assuming a one-parameter exponential family is the weakest sort of distributional assumption that can be made. The Gauss-Newton method for calculating nonlinear least squares estimates generalizes easily to deal with maximum quasi-likelihood estimates, and a rearrangement of this produces a generalization of the method described by Nelder & Wedderburn (1972).

Overview

Integrity signals

Registry

Crossref · 10.2307/2334725

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

Citations

Cited by

Sorted by citations

Items 401–500 of 509

Related

See all

Metadata

Authors
Wedderburn, R. W. M.
Affiliations
Rothamsted Research (GB)
Corresponding author
Wedderburn, R. W. M.
Venue
Biometrika
Publisher
JSTOR
Published
1974-12
Volume
61
Issue
3
Pages
439
ISSN
0006-3444 (ISSN-L)
DOI
10.2307/2334725
OpenAlex
W1979159029
Cited by
2,122
References
0
Citations by year
2026: 18 · 2025: 40 · 2024: 58 · 2023: 54 · 2022: 50 · 2021: 87 · 2020: 72 · 2019: 78 · 2018: 111 · 2017: 70 · 2016: 84 · 2015: 64 · 2014: 86 · 2013: 80 · 2012: 133
FWCI
2.12
Type
journal article
Language
en
Open access
closed
Locations
  • Biometrika (publishedVersion)
  • Rothamsted Repository (Rothamsted Repository) (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
Keywords
generalized linear models, Gauss-Newton method, exponential family, mean-variance relationship, nonlinear least squares, distributional assumptions

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