“Statistical Confluence Analysis by Means of Complete Regression Systems”
E143684
“Statistical Confluence Analysis by Means of Complete Regression Systems” is a foundational econometric work by Ragnar Frisch that develops a systematic regression-based framework for analyzing interdependent economic relationships.
All labels observed (1)
| Label | Occurrences |
|---|---|
| “Statistical Confluence Analysis by Means of Complete Regression Systems” canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1252915 — 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.
Target entity: “Statistical Confluence Analysis by Means of Complete Regression Systems” Context triple: [Ragnar Frisch, notableWork, “Statistical Confluence Analysis by Means of Complete Regression Systems”]
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A.
A Solution to the Ecological Inference Problem
A Solution to the Ecological Inference Problem is a influential methodological book by political scientist Gary King that introduces statistical techniques for inferring individual-level behavior from aggregate data.
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B.
The Probability Approach in Econometrics
The Probability Approach in Econometrics is Trygve Haavelmo’s landmark work that founded modern econometrics by rigorously formulating economic relationships within a probabilistic, statistical framework.
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C.
Gaussian law of error
The Gaussian law of error is a fundamental statistical principle stating that measurement errors tend to follow a normal (bell-shaped) distribution, forming the basis of much of probability theory and statistical inference.
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D.
Logical Foundations of Probability
Logical Foundations of Probability is a seminal philosophical work by Rudolf Carnap that develops a rigorous logical and formal account of probability and inductive reasoning.
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E.
Gauss–Markov theorem
The Gauss–Markov theorem is a fundamental result in statistics stating that, under certain conditions, the ordinary least squares estimator is the best linear unbiased estimator (BLUE) of the coefficients in a linear regression model.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: “Statistical Confluence Analysis by Means of Complete Regression Systems” Target entity description: “Statistical Confluence Analysis by Means of Complete Regression Systems” is a foundational econometric work by Ragnar Frisch that develops a systematic regression-based framework for analyzing interdependent economic relationships.
-
A.
A Solution to the Ecological Inference Problem
A Solution to the Ecological Inference Problem is a influential methodological book by political scientist Gary King that introduces statistical techniques for inferring individual-level behavior from aggregate data.
-
B.
The Probability Approach in Econometrics
The Probability Approach in Econometrics is Trygve Haavelmo’s landmark work that founded modern econometrics by rigorously formulating economic relationships within a probabilistic, statistical framework.
-
C.
Gaussian law of error
The Gaussian law of error is a fundamental statistical principle stating that measurement errors tend to follow a normal (bell-shaped) distribution, forming the basis of much of probability theory and statistical inference.
-
D.
Logical Foundations of Probability
Logical Foundations of Probability is a seminal philosophical work by Rudolf Carnap that develops a rigorous logical and formal account of probability and inductive reasoning.
-
E.
Gauss–Markov theorem
The Gauss–Markov theorem is a fundamental result in statistics stating that, under certain conditions, the ordinary least squares estimator is the best linear unbiased estimator (BLUE) of the coefficients in a linear regression model.
- F. None of above. chosen
Statements (42)
| Predicate | Object |
|---|---|
| instanceOf |
econometric methodology paper
ⓘ
econometrics book ⓘ scholarly work ⓘ |
| aim | to provide a systematic framework for analyzing interdependent economic relationships ⓘ |
| associatedWith |
Norwegian School of Economics and econometrics tradition
ⓘ
early development of econometrics as a discipline ⓘ |
| author | Ragnar Frisch ⓘ |
| contribution |
clarifies identification issues in systems of economic equations
ⓘ
develops a systematic regression-based framework for analyzing interdependent economic relationships ⓘ formalizes statistical confluence analysis in econometrics ⓘ introduces the concept of complete regression systems ⓘ links economic theory with statistical estimation in multi-equation systems ⓘ |
| describedAs | a foundational econometric work ⓘ |
| field |
econometrics
ⓘ
economic theory ⓘ statistics ⓘ |
| genre | academic monograph ⓘ |
| hasAuthor | Ragnar Frisch ⓘ |
| hasKeyConcept |
complete regression system
ⓘ
confluence analysis ⓘ interdependence of variables ⓘ |
| historicalSignificance | one of the early systematic treatments of multi-equation econometric models ⓘ |
| influenced |
development of modern econometric theory
ⓘ
econometric treatment of interdependent markets ⓘ subsequent research on simultaneous equation models ⓘ |
| influencedBy | Ragnar Frisch’s work on econometric methodology ⓘ |
| language | English ⓘ |
| mainSubject |
confluence analysis
ⓘ
interdependent economic relationships ⓘ regression analysis ⓘ simultaneous equations ⓘ |
| methodology | regression-based analysis of systems of equations ⓘ |
| relatedTo |
Ragnar Frisch’s Nobel Prize–winning contributions to econometrics
ⓘ
identification problem in econometrics ⓘ simultaneous equations econometrics ⓘ structural equation modeling in economics ⓘ |
| topic |
econometric modeling
ⓘ
economic relationships ⓘ regression systems ⓘ statistical inference in economics ⓘ |
| usedIn |
advanced econometrics
ⓘ
economic modeling of simultaneous systems ⓘ |
How these facts were elicited
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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.
Subject: “Statistical Confluence Analysis by Means of Complete Regression Systems” Description of subject: “Statistical Confluence Analysis by Means of Complete Regression Systems” is a foundational econometric work by Ragnar Frisch that develops a systematic regression-based framework for analyzing interdependent economic relationships.
Referenced by (1)
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