Mean Squared Error Estimation
Mean Squared Error Estimation is a statistical inference method that quantifies the average squared deviation between predicted and true values in small area parameters, distinguished by its focus on balancing bias and variance in finite-sample settings under complex survey designs.
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Least Median of Squares Regression
Peter J. Rousseeuw · Journal of the American Statistical Association · 1984 · 3.6K citations
Estimation of the Mean of a Multivariate Normal Distribution
Charles Stein · The Annals of Statistics · 1981 · 2.8K citations · Full text
Variable Selection for Propensity Score Models
M. Alan Brookhart, Sebastian Schneeweiß, Kenneth J. Rothman et al. · American Journal of Epidemiology · 2006 · 2.3K citations · Full text
Theory of the backpropagation neural network
Hecht-Nielsen · 1989 · 2.2K citations
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Technion – Israel Institute of Technology
Haifa, Israel
23 h-index
52 publications
4.1K citations
Massachusetts Institute of Technology
Cambridge, United States
20 h-index
40 publications
3.2K citations
Quaid-i-Azam University
Islamabad, Pakistan
19 h-index
54 publications
1.4K citations
Hacettepe University
Ankara, Türkiye
18 h-index
33 publications
1.5K citations
Purdue University West Lafayette
West Lafayette, United States
18 h-index
31 publications
2.7K citations
University of Wisconsin–Madison
Madison, United States
18 h-index
27 publications
2.1K citations

Carleton University
Ottawa, Canada
17 h-index
25 publications
2.2K citations
Iowa State University
Ames, United States
17 h-index
23 publications
1.7K citations
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