Confidence intervals for long memory regressions

Kyungduk Ko; Jaechoul Lee; Robert Lund

doi:10.1016/j.spl.2008.01.057

Confidence intervals for long memory regressions

Kyungduk Ko
, Jaechoul Lee
, Robert Lund

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

3 Scopus citations

Abstract

This paper proposes an accurate confidence interval for the trend parameter in a linear regression model with long memory errors. The interval is based upon an equivalent sum of squares method and is shown to perform comparably to a weighted least squares interval. The advantages of the proposed interval lies in its relative ease of computation and should be attractive to practitioners.

Original language	English (US)
Pages (from-to)	1894-1902
Number of pages	9
Journal	Statistics and Probability Letters
Volume	78
Issue number	13
DOIs	https://doi.org/10.1016/j.spl.2008.01.057
State	Published - Sep 15 2008
Externally published	Yes

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/j.spl.2008.01.057

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title = "Confidence intervals for long memory regressions",

abstract = "This paper proposes an accurate confidence interval for the trend parameter in a linear regression model with long memory errors. The interval is based upon an equivalent sum of squares method and is shown to perform comparably to a weighted least squares interval. The advantages of the proposed interval lies in its relative ease of computation and should be attractive to practitioners.",

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AU - Ko, Kyungduk

AU - Lee, Jaechoul

AU - Lund, Robert

PY - 2008/9/15

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N2 - This paper proposes an accurate confidence interval for the trend parameter in a linear regression model with long memory errors. The interval is based upon an equivalent sum of squares method and is shown to perform comparably to a weighted least squares interval. The advantages of the proposed interval lies in its relative ease of computation and should be attractive to practitioners.

AB - This paper proposes an accurate confidence interval for the trend parameter in a linear regression model with long memory errors. The interval is based upon an equivalent sum of squares method and is shown to perform comparably to a weighted least squares interval. The advantages of the proposed interval lies in its relative ease of computation and should be attractive to practitioners.

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UR - https://www.scopus.com/pages/publications/49649089538#tab=citedBy

U2 - 10.1016/j.spl.2008.01.057

DO - 10.1016/j.spl.2008.01.057

M3 - Article

AN - SCOPUS:49649089538

SN - 0167-7152

VL - 78

SP - 1894

EP - 1902

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

IS - 13

ER -

Confidence intervals for long memory regressions

Abstract

ASJC Scopus subject areas

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