Additive Function-on-Function Regression
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 develop a compu…
A Nonparametric Approach to Detect Nonlinear Correlation in Gene Expression
We propose a distribution-free approach to detect nonlinear relationships by reporting local correlation. The effect of our proposed method is analogous to piecewise linear approximation although t…
Spatially Adaptive Bayesian Penalized Splines With Heteroscedastic Errors
Penalized splines have become an increasingly popular tool for nonparametric smoothing because of their use of low-rank spline bases, which makes computations tractable while maintaining accuracy a…
Sparse Regression by Projection and Sparse Discriminant Analysis
Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high-dimensional data. In these approaches, the direction and length of…
Bayesian Semiparametric Density Deconvolution in the Presence of Conditionall…
We consider the problem of estimating the density of a random variable when precise measurements on the variable are not available, but replicated proxies contaminated with measurement error are av…
Semiparametric Estimation of the Distribution of Episodically Consumed Foods …
Dietary data collected from 24-hour dietary recalls are observed with significant measurement errors. In the nonparametric curve estimation literature, much of the effort has been devoted to design…
Bayesian Copula Density Deconvolution for Zero-Inflated Data in Nutritional E…
Estimating the marginal and joint densities of the long-term average intakes of different dietary components is an important problem in nutritional epidemiology. Since these variables cannot be dir…
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