15 citations · 27 across the 8 of their papers we have counts for
8 papers
Smoothness-Penalized Deconvolution (SPeD) of a Density Estimate
David Kent, David Ruppert
This paper addresses the deconvolution problem of estimating a square-integrable probability density from observations contaminated with additive measurement errors having a known…
Adaptive Ridge-Penalized Functional Local Linear Regression
Wentian Huang, David Ruppert
We introduce an original method of multidimensional ridge penalization in functional local linear regressions. The nonparametric regression of functional data is extended from its…
Measurement Errors in Semiparametric Generalized Regression Models
Mohammad W. Hattab, David Ruppert
Regression models that ignore measurement error in predictors may produce highly biased estimates leading to erroneous inferences. It is well known that it is extremely difficult t…
Density Deconvolution with Additive Measurement Errors using Quadratic Programming
Ran Yang, Daniel Apley, Jeremy Staum +1
Distribution estimation for noisy data via density deconvolution is a notoriously difficult problem for typical noise distributions like Gaussian. We develop a density deconvolutio…
Additive Function-on-Function Regression
Janet S. Kim, Ana-Maria Staicu, Arnab Maity +2
We study additive function-on-function regression where the mean response at a particular time point depends on the time point itself as well as the entire covariate trajectory. We…
Restricted Likelihood Ratio Tests for Linearity in Scalar-on-Function Regression
Mathew W. McLean, Giles Hooker, David Ruppert
We propose a procedure for testing the linearity of a scalar-on-function regression relationship. To do so, we use the functional generalized additive model (FGAM), a recently deve…
Local Asymptotics of P-splines
Luo Xiao, Yingxing Li, Tatiyana V. Apanasovich +1
This report studies local asymptotics of P-splines with th degree B-splines and a th order difference penalty. Earlier work with and restricted is extended to the gen…
Fast Bivariate Penalized Splines: the Sandwich Smoother
Luo Xiao, Yingxing Li, David Ruppert
We propose a fast penalized spline method for bivariate smoothing. Univariate P-spline smoothers (Eilers and Marx, 1996) are applied simultaneously along both coordinates. The new…