Smoothing parameters of penalized spline nonparametric regression model using linear mixed model
نویسندگان
چکیده
منابع مشابه
Use of Two Smoothing Parameters in Penalized Spline Estimator for Bi-variate Predictor Non-parametric Regression Model
Penalized spline criteria involve the function of goodness of fit and penalty, which in the penalty function contains smoothing parameters. It serves to control the smoothness of the curve that works simultaneously with point knots and spline degree. The regression function with two predictors in the non-parametric model will have two different non-parametric regression functions. Therefore, we...
متن کاملNonparametric Small Area Estimation Using Penalized Spline Regression
We propose a new small area estimation approach that combines small area random effects with a smooth, nonparametrically specified trend. By using penalized splines as the representation for the nonparametric trend, it is possible to express the small area estimation problem as a mixed effect regression model. We show how this model can be fitted using existing model fitting approaches such as ...
متن کاملExistence and Uniqueness of Penalized Least Square Estimation for Smoothing Spline Nonlinear Nonparametric Regression Models
where Ni are known nonlinear functionals, g = (g1, · · · , gr) are unknown functions, and 2i iid ∼ N(0, σ) are random errors. Without loss of generality, we assume that r = 2. As in O’Sullivan (1990), we express design points x explicitly in the functional Ni: Ni(g1, g2) = η(g1, g2; xi), where η is a known nonlinear functional. In the following sections, η(g1, g2; x) is sometimes also represent...
متن کاملModel Checking in Tobit Regression Model via Nonparametric Smoothing
A nonparametric lack-of-fit test is proposed to check the adequacy of the presumed parametric form for the regression function in Tobit regression models by applying Zheng’s device with weighted residuals. It is shown that testing the null hypothesis for the standard Tobit regression models is equivalent to test a new null hypothesis of the classic regression models. An optimal weight function ...
متن کاملModel Selection in Linear Mixed Models Using Mdl Criterion with an Application to Spline Smoothing
For spline smoothing one can rewrite the smooth estimation as a linear mixed model (LMM) where the smoothing parameter appears as the variance of spline basis coefficients. Smoothing methods that use basis functions with penalization can utilize maximum likelihood (ML) theory in LMM framework ([8]). We introduce the minimum description length (MDL) model selection criterion in LMM and propose a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IOP Conference Series: Earth and Environmental Science
سال: 2019
ISSN: 1755-1315
DOI: 10.1088/1755-1315/243/1/012040