Nonparametric model-assisted estimators have been proposed to improve estimates of finite population parameters. More efficient estimators are obtained when the parametric model is misspecified due to the flexibility of nonparametric models. In this dissertation, we derive information criteria to select appropriate auxiliary variables to use in an additive model-assisted method....
Monotone additive models are useful in estimating productivity curves or analyzing disease risk where the predictors are known to have monotonic effects on the response. Existing literature mainly focuses on univariate monotone smoothing. Available methods for the estimation of monotone additive models are either difficult to interpret or have no...
We consider two semiparametric regression models for data analysis, the stochastic additive model (SAM) for nonlinear time series data and the additive coefficient model (ACM) for randomly sampled data with nonparametric structure. We employ the SCAD-penalized polynomial spline estimation method for estimation and simultaneous variable selection in both models. It...
This study deals specifically with classical cubic splines. Based on
a lemma of John Rice, best approximation in the uniform norm by
cubic splines is explored. The purpose of this study is to
characterize the best approximation to a given continuous function
f(x) by a cubic spline with fixed knots...