Reducing the effects of collinearity in regression of heat transfer data

N Brauner; M Shacham

Reducing the effects of collinearity in regression of heat transfer data

Department of Chemical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Collinearity among dimensionless groups of the-independent variables may often prevent obtaining statistically valid, reliable correlations. In this paper commonly used collinearity indicators (such as condition number of the normal matrix, variance inflation factor and confidence intervals) and a new indicator," truncation error to noise ratio"(TNR) are used to investigate the level of collinearity and its harmful effects.

Original language	English
Title of host publication	HEAT TRANSFER 1998, VOL 4
Pages	3-8
State	Published - 1998

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title = "Reducing the effects of collinearity in regression of heat transfer data",

abstract = "Collinearity among dimensionless groups of the-independent variables may often prevent obtaining statistically valid, reliable correlations. In this paper commonly used collinearity indicators (such as condition number of the normal matrix, variance inflation factor and confidence intervals) and a new indicator,{"} truncation error to noise ratio{"}(TNR) are used to investigate the level of collinearity and its harmful effects.",

author = "N Brauner and M Shacham",

year = "1998",

language = "English",

pages = "3--8",

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TY - CHAP

T1 - Reducing the effects of collinearity in regression of heat transfer data

AU - Brauner, N

AU - Shacham, M

PY - 1998

Y1 - 1998

N2 - Collinearity among dimensionless groups of the-independent variables may often prevent obtaining statistically valid, reliable correlations. In this paper commonly used collinearity indicators (such as condition number of the normal matrix, variance inflation factor and confidence intervals) and a new indicator," truncation error to noise ratio"(TNR) are used to investigate the level of collinearity and its harmful effects.

AB - Collinearity among dimensionless groups of the-independent variables may often prevent obtaining statistically valid, reliable correlations. In this paper commonly used collinearity indicators (such as condition number of the normal matrix, variance inflation factor and confidence intervals) and a new indicator," truncation error to noise ratio"(TNR) are used to investigate the level of collinearity and its harmful effects.

M3 - Chapter

SP - 3

EP - 8

BT - HEAT TRANSFER 1998, VOL 4

ER -

Reducing the effects of collinearity in regression of heat transfer data

Abstract

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