Functional Measurement Error Models is a class of statistical models within the broader category of measurement error models that assumes the true covariates are fixed but unknown quantities, distinguishing it from structural measurement error models where covariates are treated as random variables with specified distributions.
27
Publications
1.3K
Citations
49
Authors
38
Institutions
Publications per year
2017–2026
3
Variants
Functional Measurement Error Model
Publications
27
Regression and functional relations
R. Webster · European Journal of Soil Science · 1997 · 128 citations
Regression and functional relations
R. Webster · European Journal of Soil Science · 1997 · 64 citations
1–5 of 27
Authors
49
- RJ
5
h-index
- YM
4
h-index
- PG
2
h-index
- GY
2
h-index
- KL
1
h-index
1–5 of 49
Institutions
38
Texas A&M University
College Station, United States
6 h-index
12 publications
371 citations
University of Waterloo
Waterloo, Canada
3 h-index
4 publications
121 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
2 h-index
2 publications
299 citations
United States Census Bureau
Suitland, United States
2 h-index
4 publications
186 citations
North Carolina State University
Raleigh, United States
2 h-index
2 publications
342 citations
RTI International
Durham, United States
1 h-index
1 publications
15 citations
University of California San Diego
San Diego, United States
1 h-index
1 publications
90 citations
Faculty of Public Health
London, United Kingdom
1 h-index
1 publications
20 citations
1–8 of 38
Venues
- Journal of the American Statistical Association
4 publications · 105 citations
4
h-index
- European Journal of Soil Science
2 publications · 192 citations
2
h-index
- Journal of the Royal Statistical Society Series B (Statistical Methodology)
2 publications · 54 citations
2
h-index
- Biometrika
2 publications · 342 citations
2
h-index
- Biometrics
1 publications · 25 citations
1
h-index
1–5