Semiparametric Density Estimation
Semiparametric Density Estimation is a statistical method that combines parametric and nonparametric components to model the overall structure of a probability density function with partial assumptions about its form, allowingflexible inference while retaining efficiency.
109
Publications
6.8K
Citations
199
Authors
132
Institutions
Publications per year
2017–2026
12
109
A Smoothed Maximum Score Estimator for the Binary Response Model
Joël L. Horowitz · Econometrica · 1992 · 602 citations
Locally parametric nonparametric density estimation
Nils Lid Hjort, M. C. Jones · The Annals of Statistics · 1996 · 323 citations · Full text
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National Institute of Allergy and Infectious Diseases, United States
3 publications · 234 citations
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1–5 of 199
132
Stanford University
Stanford, United States
4 h-index
6 publications
188 citations
University of Maryland, College Park
College Park, United States
4 h-index
8 publications
418 citations
UCLouvain
Louvain-la-Neuve, Belgium
4 h-index
7 publications
139 citations
Texas A&M University
College Station, United States
3 h-index
9 publications
188 citations
University of Michigan
Ann Arbor, United States
3 h-index
5 publications
71 citations
Duke University
Durham, United States
3 h-index
3 publications
94 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
5 publications
141 citations
National Institutes of Health
Bethesda, United States
3 h-index
3 publications
67 citations
1–8 of 132
10 publications · 1K citations
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8 publications · 1.5K citations
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Repository · 6 publications · 186 citations
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5 publications · 776 citations
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4 publications · 106 citations
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