Result: M-type smoothing splines in nonparametric and semiparametric regression models

Title:
M-type smoothing splines in nonparametric and semiparametric regression models
Authors:
Gao, JT, Shi, PD
Contributors:
QUEENSLAND UNIV TECHNOL,SCH MATH,BRISBANE,QLD 4001,AUSTRALIA., BEIJING UNIV,DEPT PROBABIL & STAT,BEIJING 100852,PEOPLES R CHINA.
Source:
SCI
Publisher Information:
statistica sinica
Publication Year:
1997
Collection:
Peking University Institutional Repository (PKU IR) / 北京大学机构知识库
Subject Terms:
asymptotic normality, M-estimation, nonparametotic regression model, semiparametric regression model, spline smoothing technique, CONVEX DISCREPANCY FUNCTION, M-ESTIMATORS, ASYMPTOTIC-BEHAVIOR, LINEAR-MODEL, PARAMETERS, CONVERGENCE, NORMALITY, GOODNESS, TESTS, RATES
Document Type:
Academic journal journal/newspaper
Language:
English
Relation:
1022945; http://hdl.handle.net/20.500.11897/401692; WOS:A1997YF24300022
Availability:
https://hdl.handle.net/20.500.11897/401692
Accession Number:
edsbas.6F8C8159
Database:
BASE

Further Information

Consider the regression model Y-i = g(t(i)) + e(i) for i = 1,., n. Here -infinity < Y-i, e(i) < infinity, t(i) is an element of T subset of R-d, g is an element of H, and H is a specified class of continuous functions from T to R. Based on a finite series expansion (g) over tilde(n) of g, an ill-estimate (g) over cap(n) of g is constructed, and the asymptotic normality of the estimate is investigated. Meansvhile, a test statistic for testing H-0: g(.) = go(.) (a known function) is discussed. We also consider M-estimates for semiparametric regression models and show that they are consistent and asymptotically normal. ; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:A1997YF24300022&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Statistics & Probability ; SCI(E) ; 16 ; ARTICLE ; 4 ; 1155-1169 ; 7