Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 3,154

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations

Higham, Desmond J.·2001·SIAM Review

Abstract

Abstract. A practical and accessible introduction to numerical methods for stochastic differential equations is given. The reader is assumed to be familiar with Euler’s method for deterministic differential equations and to have at least an intuitive feel for the concept of a random variable; however, no knowledge of advanced probability theory or stochastic processes is assumed. The article is built around 10 MATLAB programs, and the topics covered include stochastic integration, the Euler–Maruyama method, Milstein’s method, strong and weak convergence, linear stability, and the stochastic chain rule.

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 · 10.1137/s0036144500378302

Cites

13 of 13 references verified0 citation errors · 0 not checkable

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

Cites

Show all 13 references

Cited by

See all 3,154

Metadata

Authors
Higham, D. J.
Venue
SIAM Review
Published
2001-01-01
Volume
43
Issue
3
Pages
525-546
ISSN
  • 0036-1445 (ISSN-L)
  • 1095-7200
OpenAlex
W2145137020
Cited by
3,154
References
13
FWCI
16.28
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: An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations. https://app.cochat.ai/papers/10.1137/s0036144500378302
The paper
Higham, D. J. (2001). An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations. SIAM Review. https://doi.org/10.1137/s0036144500378302

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.