Model Adequacy
Model Adequacy is the extent to which a statistical model sufficiently captures the underlying structure and patterns of observed data, as evaluated through Bayesian posterior predictive checks and comparative assessment against alternative models.
289
Publications
32.4K
Citations
642
Authors
330
Institutions
Publications per year
2017–2026
59
289
Introduction to Linear Regression Analysis.
Renato Assunção, Paul D. Sampson, Douglas C. Montgomery et al. · Journal of the American Statistical Association · 1993 · 5.4K citations
Robert F. Engle, Simone Manganelli · Journal of Business and Economic Statistics · 2004 · 2.2K citations
Management, Finance, Risk Management +17
Operational testing of hydrological simulation models
V. Klemeš · Hydrological Sciences Journal · 1986 · 1.4K citations · Full text
Assessment of the adequacy of mathematical models
Luís O Tedeschi · Agricultural Systems · 2006 · 740 citations
1–5 of 289
642
5
h-index
4
h-index
3
h-index
Hong Kong University of Science and Technology, Hong Kong SAR China
3 publications · 334 citations
3
h-index
3
h-index
1–5 of 642
330

University of Hong Kong
Pok Fu Lam, Hong Kong
6 h-index
11 publications
1.8K citations

The University of Sydney
Sydney, Australia
5 h-index
10 publications
426 citations

UNSW Sydney
Sydney, Australia
5 h-index
6 publications
1.6K citations
United States Geological Survey
Reston, United States
4 h-index
6 publications
810 citations
University of Florida
Gainesville, United States
4 h-index
8 publications
375 citations

Chinese Academy of Sciences
Beijing, China
4 h-index
9 publications
280 citations

University of Oslo
Oslo, Norway
4 h-index
8 publications
238 citations
Virginia Tech
Blacksburg, United States
4 h-index
5 publications
184 citations
1–8 of 330
12 publications · 6.4K citations
12
h-index
9 publications · 779 citations
9
h-index
7 publications · 1.4K citations
7
h-index
6 publications · 1.3K citations
6
h-index
5 publications · 182 citations
5
h-index
1–5