A note on fitting a regression without an intercept term

Douglas M. Hawkins

doi:10.1080/00031305.1980.10483035

A note on fitting a regression without an intercept term

Douglas M. Hawkins

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

4 Scopus citations

Abstract

By entering the data (-y_i, -x_i) followed by (-y_i-x_i), one can obtain an intercept-free regression Y = Xβ + ε from a program package that normally uses an intercept term. There is no bias in the resultant regression coefficients, but a minor postanalysis adjustment is needed to the residual variance and standard errors.

Original language	English (US)
Pages (from-to)	233
Number of pages	1
Journal	American Statistician
Volume	34
Issue number	4
DOIs	https://doi.org/10.1080/00031305.1980.10483035
State	Published - Nov 1980
Externally published	Yes

Bibliographical note

Funding Information:
If X" ... , X n are identically and independently distributed, then as n --> 00, there exists under suitable regularity conditions a sequence of solutions of the likelihood equation that is consistent and asymptotically efficient. However, this consistent solution is not necessarily the maximum likelihood estimate. Likelihood estimation should therefore emphasize the determination of a consistent sequence of * ~.L. Lehmann is Professor of Statistics, University of California, Berkeley, CA 94720. This article was prepared with the support of National Science Foundation Grant MCS76-1-238 and Office of Naval Research Contract No. N-14-75-C-0444/Nr 042-036.

Keywords

Intercept
Multiple regression
Program packages

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10.1080/00031305.1980.10483035

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title = "A note on fitting a regression without an intercept term",

abstract = "By entering the data (-yi, -xi) followed by (-yi-xi), one can obtain an intercept-free regression Y = Xβ + ε from a program package that normally uses an intercept term. There is no bias in the resultant regression coefficients, but a minor postanalysis adjustment is needed to the residual variance and standard errors.",

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PY - 1980/11

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N2 - By entering the data (-yi, -xi) followed by (-yi-xi), one can obtain an intercept-free regression Y = Xβ + ε from a program package that normally uses an intercept term. There is no bias in the resultant regression coefficients, but a minor postanalysis adjustment is needed to the residual variance and standard errors.

AB - By entering the data (-yi, -xi) followed by (-yi-xi), one can obtain an intercept-free regression Y = Xβ + ε from a program package that normally uses an intercept term. There is no bias in the resultant regression coefficients, but a minor postanalysis adjustment is needed to the residual variance and standard errors.

KW - Intercept

KW - Multiple regression

KW - Program packages

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JF - American Statistician

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ER -

A note on fitting a regression without an intercept term

Abstract

Bibliographical note

Keywords

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