Structural inference for linear regression with autocorrelated errors

B. Reiser

doi:10.1007/BF02922918

Structural inference for linear regression with autocorrelated errors

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

Abstract

Methods of structural inference are applied to the linear regression model in which the errors follow an autoregressive process. A marginal likelihood function is derived for the autoregressive parameters while structural distributions are obtained for the regression parameters. The marginal likelihood function, in the case of a Markov error process, is shown to be related under certain conditions to the Durbin-Watsonstatistic. This method of inference is illustrated by a simulated example.

Original language	English
Pages (from-to)	85-104
Number of pages	20
Journal	Statistische Hefte
Volume	16
Issue number	2
DOIs	https://doi.org/10.1007/BF02922918
State	Published - Jun 1975
Externally published	Yes

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1007/BF02922918

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title = "Structural inference for linear regression with autocorrelated errors",

abstract = "Methods of structural inference are applied to the linear regression model in which the errors follow an autoregressive process. A marginal likelihood function is derived for the autoregressive parameters while structural distributions are obtained for the regression parameters. The marginal likelihood function, in the case of a Markov error process, is shown to be related under certain conditions to the Durbin-Watsonstatistic. This method of inference is illustrated by a simulated example.",

author = "B. Reiser",

year = "1975",

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journal = "Statistische Hefte",

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AB - Methods of structural inference are applied to the linear regression model in which the errors follow an autoregressive process. A marginal likelihood function is derived for the autoregressive parameters while structural distributions are obtained for the regression parameters. The marginal likelihood function, in the case of a Markov error process, is shown to be related under certain conditions to the Durbin-Watsonstatistic. This method of inference is illustrated by a simulated example.

UR - https://www.scopus.com/pages/publications/52449140298

U2 - 10.1007/BF02922918

DO - 10.1007/BF02922918

M3 - Article

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SP - 85

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JO - Statistische Hefte

JF - Statistische Hefte

IS - 2

ER -

Structural inference for linear regression with autocorrelated errors

Abstract

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