Electronic Journal of Statistics
E833561
The Electronic Journal of Statistics is a peer-reviewed open-access journal publishing research articles in statistics and related fields.
All labels observed (2)
| Label | Occurrences |
|---|---|
| Electron. J. Stat. | 1 |
| Electronic Journal of Statistics canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T9986337 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Electronic Journal of Statistics Context triple: [Institute of Mathematical Statistics, hasJournal, Electronic Journal of Statistics]
-
A.
Journal of the American Statistical Association
The Journal of the American Statistical Association is a leading peer-reviewed scholarly journal covering theoretical and applied statistics across a wide range of scientific disciplines.
-
B.
Journal of Business & Economic Statistics
The Journal of Business & Economic Statistics is a leading peer-reviewed academic journal focusing on the development and application of statistical methods in business, finance, and economics.
-
C.
The American Statistician
The American Statistician is a peer-reviewed journal that features articles on statistical practice, theory, and education, published by the American Statistical Association.
-
D.
Institute of Mathematical Statistics
The Institute of Mathematical Statistics is a leading international professional society dedicated to the development and dissemination of theory and applications in statistics and probability.
-
E.
JMLR
JMLR (Journal of Machine Learning Research) is a leading peer-reviewed academic journal focusing on cutting-edge research in machine learning and related fields.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Electronic Journal of Statistics Target entity description: The Electronic Journal of Statistics is a peer-reviewed open-access journal publishing research articles in statistics and related fields.
-
A.
Journal of the American Statistical Association
The Journal of the American Statistical Association is a leading peer-reviewed scholarly journal covering theoretical and applied statistics across a wide range of scientific disciplines.
-
B.
Journal of Business & Economic Statistics
The Journal of Business & Economic Statistics is a leading peer-reviewed academic journal focusing on the development and application of statistical methods in business, finance, and economics.
-
C.
The American Statistician
The American Statistician is a peer-reviewed journal that features articles on statistical practice, theory, and education, published by the American Statistical Association.
-
D.
Institute of Mathematical Statistics
The Institute of Mathematical Statistics is a leading international professional society dedicated to the development and dissemination of theory and applications in statistics and probability.
-
E.
JMLR
JMLR (Journal of Machine Learning Research) is a leading peer-reviewed academic journal focusing on cutting-edge research in machine learning and related fields.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
academic journal
ⓘ
scientific journal ⓘ |
| academicDiscipline |
applied statistics
ⓘ
biostatistics ⓘ probability theory ⓘ statistical methodology ⓘ statistics ⓘ theoretical statistics ⓘ |
| accessPolicy | free to read ⓘ |
| countryOfPublication |
United States
ⓘ
linked to:
United States of America
|
| format |
HTML
ⓘ
PDF ⓘ |
| hasAbbreviation |
EJS
ⓘ
Electron. J. Stat. ⓘ
linked to:
Electronic Journal of Statistics
|
| hasArticleProcessingCharges | no (for readers) ⓘ |
| hasContentType |
case studies
ⓘ
original research ⓘ surveys ⓘ |
| hasDigitalArchive | yes ⓘ |
| hasDisciplineCategory |
mathematics
ⓘ
statistics and probability ⓘ |
| hasFormat | online journal articles ⓘ |
| hasISSN | 1935-7524 ⓘ |
| hasPeerReview | yes ⓘ |
| hasPublicationFrequency | continuous ⓘ |
| hasWebsite | https://projecteuclid.org/journals/electronic-journal-of-statistics ⓘ |
| isAvailableOnline | yes ⓘ |
| isIndexedIn |
Mathematical Reviews
ⓘ
linked to:
Mathematical Reviews database
Scopus ⓘ Web of Science ⓘ Zentralblatt MATH ⓘ |
| isOpenAccess | true ⓘ |
| isPeerReviewed | true ⓘ |
| language | English ⓘ |
| licensePolicy | open-access license ⓘ |
| medium | electronic ⓘ |
| peerReviewProcess | single-blind ⓘ |
| publicationType | online-only ⓘ |
| publisher | Institute of Mathematical Statistics ⓘ |
| publishes |
methodological papers
ⓘ
research articles ⓘ review articles ⓘ |
| startYear | 2007 ⓘ |
| subjectArea | statistics and related fields ⓘ |
| targetAudience |
applied statisticians
ⓘ
mathematicians ⓘ researchers in statistics ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Electronic Journal of Statistics Description of subject: The Electronic Journal of Statistics is a peer-reviewed open-access journal publishing research articles in statistics and related fields.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: Electronic Journal of Statistics