Bayesian Error-in-variables Models
Bayesian Error-In-Variables Models is a statistical modeling framework that belongs to the class of Bayesian regression models and specifically accounts for measurement errors in both dependent and independent variables by incorporating prior distributions on latent true values to correct estimation bias.
51
Publications
3.8K
Citations
114
Authors
83
Institutions
Publications per year
2017–2026
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83

University of Waterloo
Waterloo, Canada
3 h-index
6 publications
302 citations
The Ohio State University
Columbus, United States
3 h-index
3 publications
96 citations
Universidade de São Paulo
São Paulo, Brazil
3 h-index
9 publications
137 citations
University of Connecticut
Storrs, United States
2 h-index
4 publications
84 citations
University of Washington
Seattle, United States
2 h-index
2 publications
306 citations
CSIRO Oceans and Atmosphere
Canberra, Australia
2 h-index
4 publications
476 citations

Cleveland State University
Cleveland, United States
2 h-index
2 publications
46 citations

University of British Columbia
Vancouver, Canada
2 h-index
2 publications
36 citations
1–8 of 83
3 publications · 59 citations
3
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3 publications · 256 citations
3
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3 publications · 499 citations
3
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3 publications · 76 citations
3
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2 publications · 36 citations
2
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1–5