Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 205

The DOI matches its Crossref record.

The estimation of second-order tensors, with related tests and designs

HEXT, GEORGE R.·1963·Biometrika

Abstract

The tensors considered in this paper are the linear relationships between certain pairs of physical vector quantities which may be described by 3 × 3 symmetric matrices. Such a linear relationship may well vary from point to point in a non-homogeneous medium. From measurements at a given point in the medium, the least squares estimates of the components of the tensor at that point are obtained; from these the tensor's principal axes may be estimated. On the assumption that the errors of measurement are small and normally distributed, confidence intervals for the lengths of the principal axes are derived, together with confidence regions on the unit sphere for the directions of these axes. Tests for equality of pairs of principal axes, for isotropy, and for comparing the tensors at two or more points are given. In certain common experimental situations, a design for this work may be represented by a set of points on the unit sphere. If such a design is rotatable (Box & Hunter, 1957), the estimates have optimum properties, and the confidence intervals and regions take on particularly simple forms. Seven rotatable designs are given, which should cover most practical requirements. These results are illustrated with a numerical example and diagram, taken from recent work on rock magnetism. Finally, all the results are extended to more general symmetric matrices, and some further rotatable designs are given.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/biomet/50.3-4.353

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.

A few free checks a day · papers already verified open instantly · results are public

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

See all 205

Metadata

Authors
HEXT, G. R.
Venue
Biometrika
Published
1963
Volume
50
Issue
3-4
Pages
353-373
ISSN
  • 0006-3444 (ISSN-L)
  • 1464-3510
OpenAlex
W1978716718
Cited by
205
References
0
FWCI
0.75
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: The estimation of second-order tensors, with related tests and designs. https://app.cochat.ai/papers/10.1093/biomet/50.3-4.353
The paper
HEXT, G. R. (1963). The estimation of second-order tensors, with related tests and designs. Biometrika. https://doi.org/10.1093/biomet/50.3-4.353

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.