David Ruppert

David Ruppert

Cornell University

H-index: 70

North America-United States

About David Ruppert

David Ruppert, With an exceptional h-index of 70 and a recent h-index of 39 (since 2020), a distinguished researcher at Cornell University, specializes in the field of Statistics, Operations Research, Data Science.

His recent articles reflect a diverse array of research interests and contributions to the field:

Smoothness-Penalized Deconvolution (SPeD) of a Density Estimate

Bootstrap inference for quantile-based modal regression

Ensemble Subset Regression (ENSURE): Efficient High-dimensional Prediction

Maximizing Portfolio Predictability with Machine Learning

Bayesian Functional Principal Components Analysis via Variational Message Passing with Multilevel Extensions

Splines'n Lines: Rest-frame galaxy spectral energy distributions via Bayesian functional data analysis

Proteomics and cytokine analyses distinguish myalgic encephalomyelitis/chronic fatigue syndrome cases from controls

Model checking for logistic models when the number of parameters tends to infinity

David Ruppert Information

University

Position

Andrew Schultz Professor of Engineering Professor of Statistical Science

Citations(all)

33541

Citations(since 2020)

7891

Cited By

29310

hIndex(all)

70

hIndex(since 2020)

39

i10Index(all)

158

i10Index(since 2020)

91

Email

University Profile Page

Google Scholar

David Ruppert Skills & Research Interests

Statistics

Operations Research

Data Science

Top articles of David Ruppert

Title

Journal

Author(s)

Publication Date

Smoothness-Penalized Deconvolution (SPeD) of a Density Estimate

Journal of the American Statistical Association

David Kent

David Ruppert

2023/11/8

Bootstrap inference for quantile-based modal regression

Journal of the American Statistical Association

Tao Zhang

Kengo Kato

David Ruppert

2021/5/26

Ensemble Subset Regression (ENSURE): Efficient High-dimensional Prediction

Statistica Sinica

Rong Zhu

Hua Liang

David Ruppert

2023/1/1

Maximizing Portfolio Predictability with Machine Learning

M Pinelis

Ruppert D

2023/11/3

Bayesian Functional Principal Components Analysis via Variational Message Passing with Multilevel Extensions

Bayesian Analysis

Tui H Nolan

Jeff Goldsmith

David Ruppert

2023/1

Splines'n Lines: Rest-frame galaxy spectral energy distributions via Bayesian functional data analysis

arXiv preprint arXiv:2310.19340

David Kent

Tamás Budavári

Thomas J Loredo

David Ruppert

2023/10/30

Proteomics and cytokine analyses distinguish myalgic encephalomyelitis/chronic fatigue syndrome cases from controls

Journal of Translational Medicine

Ludovic Giloteaux

Jiayin Li

Mady Hornig

W Ian Lipkin

David Ruppert

...

2023/5/13

Model checking for logistic models when the number of parameters tends to infinity

Journal of Computational and Graphical Statistics

Xinmin Li

Feifei Chen

Hua Liang

David Ruppert

2023/1/2

Measurement errors in semi‐parametric generalised regression models

Australian & New Zealand Journal of Statistics

Mohammad W Hattab

David Ruppert

2023/12

Machine learning portfolio allocation

The Journal of Finance and Data Science

Michael Pinelis

David Ruppert

2021/12/23

A semiparametric risk score for physical activity

Statistics in medicine

Erjia Cui

E Christi Thompson

Raymond J Carroll

David Ruppert

2022/3/30

A projection-based consistent test incorporating dimension-reduction in partially linear models

Statistica Sinica

Zhihua Sun

Feifei Chen

Hua Liang

David Ruppert

2021/1/1

Adaptive Ridge-Penalized Functional Local Linear Regression

arXiv preprint arXiv:2109.08308

Wentian Huang

David Ruppert

2021/9/17

Photometric redshifts via Bayesian functional data analysis

American Astronomical Society Meeting Abstracts

T Loredo

T Budavari

D Kent

D Ruppert

2021/1

Bias-corrected estimation of the density of a conditional expectation in nested simulation problems

ACM Transactions on Modeling and Computer Simulation (TOMACS)

Ran Yang

David Kent

Daniel W Apley

Jeremy Staum

David Ruppert

2021/7/23

Partial functional partially linear single-index models

Statistica Sinica

Qingguo Tang

Linglong Kong

David Ruppert

Rohana J Karunamuni

2021

A mixed model approach to measurement error in semiparametric regression

Statistics and Computing

Mohammad W Hattab

David Ruppert

2021/5

Density estimation on a network

Computational statistics & data analysis

Yang Liu

David Ruppert

2021/4/1

Optimal sampling for generalized linear models under measurement constraints

Journal of Computational and Graphical Statistics

Tao Zhang

Yang Ning

David Ruppert

2021/1/2

Iterative Likelihood: A Unified Inference Tool

Journal of Computational and Graphical Statistics

Haiying Wang

Dixin Zhang

Hua Liang

David Ruppert

2021/10/2

See List of Professors in David Ruppert University(Cornell University)

Co-Authors

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