✦ LIBER ✦

On spline estimators and prediction intervals in nonparametric regression

✍ Scribed by Kjell Doksum; Ja-Yong Koo

Publisher: Elsevier Science
Year: 2000
Tongue: English
Weight: 213 KB
Volume: 35
Category: Article
ISSN: 0167-9473
DOI: 10.1016/s0167-9473(99)00116-4

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

A note on the consistent estimator of no

A note on the consistent estimator of nonparametric regression constructed by splines

✍ Li-Xing Zhu 📂 Article 📅 1992 🏛 Elsevier Science 🌐 English ⚖ 244 KB

In this paper, we construct a consistent estimstor of nonparametric regression by spline functions, an~point out that a key theorem of Quidels's is wrong.

Prediction Intervals in Nonlinear Regres

Prediction Intervals in Nonlinear Regression

✍ Dr. A. H. Pooi 📂 Article 📅 1991 🏛 John Wiley and Sons 🌐 English ⚖ 484 KB

By treating the nonlinear model as if it were linear in the parameterization 8 in the neighbourhood of the least squares estimate 8, we construct two-sided nominally-q-prediction intervals by applying the usual linear model theory. The derivation of the truncated series expansion of the expected cov

On the Boundary Behaviour of Nonparametr

On the Boundary Behaviour of Nonparametric Regression Estimators

✍ Dr. H. Dette 📂 Article 📅 1992 🏛 John Wiley and Sons 🌐 English ⚖ 564 KB

In this note the nonparametnc regression estimators of NADARAYA (1964) and WATSON (1964). PRIESTLEY & CIUO (1972) and GASSER & MI~LLER (1979) are compared with respect to the boundary behaviour in the case of a fixed design. It is shown that the estimator of Nadaraya & Watson yields estimates with s

On Confidence Intervals in Nonparametric

On Confidence Intervals in Nonparametric Binary Regression via Edgeworth Expansions

✍ M.Celia Rodrı́guez-Campos 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 197 KB

Local confidence intervals for regression function with binary response variable are constructed. These intervals are based on both theoretical and ``plug-in'' normal asymptotic distribution of a usual statistic. In the plug-in approach, two ways of estimating bias are proposed; for them we obtain t

Adjustment of Prediction Intervals in No

Adjustment of Prediction Intervals in Nonlinear Regression

✍ K. L. Goh; A. H. Pooi 📂 Article 📅 1997 🏛 John Wiley and Sons 🌐 English ⚖ 472 KB

Consistency of error density and distrib

Consistency of error density and distribution function estimators in nonparametric regression

✍ Fuxia Cheng 📂 Article 📅 2002 🏛 Elsevier Science 🌐 English ⚖ 140 KB

This paper considers the problem of estimating the error density and distribution function in nonparametric regression models. Su cient conditions are given under which the histogram error density estimator based on nonparametric residuals is uniformly weakly and strongly consistent, and L 1 -consis