Estimating error correlation in nonparametric regression

Naomi Simone Altman

doi:10.1016/0167-7152(93)90219-9

Estimating error correlation in nonparametric regression

Naomi Simone Altman

Statistics

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

Estimates of error correlations in kernel nonparametric regression are obtained using the method of moments. A high order asymptotic expansion of the estimators shows that they are consistent and asymptotically normal at parametric rates, and provides heuristics for the choice of bandwidth and kernel.

Original language	English (US)
Pages (from-to)	213-218
Number of pages	6
Journal	Statistics and Probability Letters
Volume	18
Issue number	3
DOIs	https://doi.org/10.1016/0167-7152(93)90219-9
State	Published - Oct 15 1993

All Science Journal Classification (ASJC) codes

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/0167-7152(93)90219-9

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title = "Estimating error correlation in nonparametric regression",

abstract = "Estimates of error correlations in kernel nonparametric regression are obtained using the method of moments. A high order asymptotic expansion of the estimators shows that they are consistent and asymptotically normal at parametric rates, and provides heuristics for the choice of bandwidth and kernel.",

author = "Altman, \{Naomi Simone\}",

note = "Funding Information: This work was supported by a Natural Sciences and Engineering Research Council of Canada Grant 151410 NYF. Much of this work was completed while the author was in the Department",

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AU - Altman, Naomi Simone

N1 - Funding Information: This work was supported by a Natural Sciences and Engineering Research Council of Canada Grant 151410 NYF. Much of this work was completed while the author was in the Department

PY - 1993/10/15

Y1 - 1993/10/15

N2 - Estimates of error correlations in kernel nonparametric regression are obtained using the method of moments. A high order asymptotic expansion of the estimators shows that they are consistent and asymptotically normal at parametric rates, and provides heuristics for the choice of bandwidth and kernel.

AB - Estimates of error correlations in kernel nonparametric regression are obtained using the method of moments. A high order asymptotic expansion of the estimators shows that they are consistent and asymptotically normal at parametric rates, and provides heuristics for the choice of bandwidth and kernel.

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UR - https://www.scopus.com/pages/publications/38249001266#tab=citedBy

U2 - 10.1016/0167-7152(93)90219-9

DO - 10.1016/0167-7152(93)90219-9

M3 - Article

AN - SCOPUS:38249001266

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VL - 18

SP - 213

EP - 218

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

IS - 3

ER -

Estimating error correlation in nonparametric regression

Abstract

All Science Journal Classification (ASJC) codes

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