Heteroscedastic Error Models is a statistical modeling framework that belongs to the class of error models in regression analysis and is distinguished by its explicit accommodation of non-constant variance in the error terms across levels of independent variables.
811
Publications
120.7K
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1.2K
Authors
641
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Publications per year
2017–2026
90
Publications
811
Henry Scheffé · Soil Science · 1960 · 5.6K citations
A Simple Test for Heteroscedasticity and Random Coefficient Variation
Trevor Breusch, A. R. Pagan · Econometrica · 1979 · 5.4K citations
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Authors
1.2K
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14
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8
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1–5 of 1.2K
Institutions
641
University of Southern California
Los Angeles, United States
16 h-index
26 publications
1.5K citations
Texas A&M University
College Station, United States
13 h-index
19 publications
1.5K citations
Universidade de São Paulo
São Paulo, Brazil
12 h-index
22 publications
862 citations
Universidade Federal de Pernambuco
Recife, Brazil
11 h-index
18 publications
1.6K citations
Michigan State University
East Lansing, United States
11 h-index
16 publications
4.4K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
11 h-index
17 publications
2.2K citations
Cornell University
Ithaca, United States
11 h-index
20 publications
1.9K citations
University of Hong Kong
Pok Fu Lam, Hong Kong
9 h-index
10 publications
211 citations
1–8 of 641
Venues
- Journal of the American Statistical Association
63 publications · 6.8K citations
34
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- Journal of Econometrics
41 publications · 5.2K citations
26
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- Econometrica
25 publications · 53.2K citations
22
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- Journal of Statistical Planning and Inference
23 publications · 580 citations
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- Biometrika
22 publications · 2K citations
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