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David Ruppert
Researcher at Cornell University
Publications - 256
Citations - 30792
David Ruppert is an academic researcher from Cornell University. The author has contributed to research in topics: Estimator & Nonparametric regression. The author has an hindex of 61, co-authored 252 publications receiving 27137 citations. Previous affiliations of David Ruppert include University of Vermont & University of North Carolina at Chapel Hill.
Papers
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Book ChapterDOI
Factor Models and Principal Components
David Ruppert,David S. Matteson +1 more
TL;DR: In this chapter, two closely related techniques, factor analysis and principal components analysis, often called PCA, are studied.
Smoothness-Penalized Deconvolution (SPeD) of a Density Estimate
D. V. Kent,David Ruppert +1 more
TL;DR: In this paper , a smoothness-penalized estimator is proposed to estimate a square-integrable probability density from observations contaminated with additive measurement errors having a known density.
Journal ArticleDOI
A mixed model approach to measurement error in semiparametric regression
Mohammad W. Hattab,David Ruppert +1 more
TL;DR: This paper proposed an approach to deal with measurement errors in predictors when modelling flexible regression functions by directly modeling the mean and the variance of the response variable after integrating out the true unobserved predictors in a penalized splines model.
Posted Content
Adaptive Ridge-Penalized Functional Local Linear Regression
Wentian Huang,David Ruppert +1 more
TL;DR: In this paper, a data-adaptive ridge penalty is proposed to adjust the structure of the penalty according to the data sets, which enables a quadratic programming search for optimal tuning parameters that minimize the estimated mean squared error (MSE).
Book ChapterDOI
Regression: Advanced Topics
David Ruppert,David S. Matteson +1 more
TL;DR: In this paper, the authors propose to replace the assumption of independent noise by the weaker assumption that the noise process is station-ary but possibly correlated, which is the strategy we will discuss in this section.