University of Hertfordshire

Multiple Neutral Regression

Research output: Working paper

Standard

Multiple Neutral Regression. / Tofallis, C.

University of Hertfordshire, 2000. (Business School Working Papers; Vol. UHBS 2000-13), (Operational Research Paper; Vol. 14).

Research output: Working paper

Harvard

Tofallis, C 2000 'Multiple Neutral Regression' Business School Working Papers, vol. UHBS 2000-13, Operational Research Paper, vol. 14, University of Hertfordshire.

APA

Tofallis, C. (2000). Multiple Neutral Regression. (Business School Working Papers; Vol. UHBS 2000-13), (Operational Research Paper; Vol. 14). University of Hertfordshire.

Vancouver

Tofallis C. Multiple Neutral Regression. University of Hertfordshire. 2000. (Business School Working Papers). (Operational Research Paper).

Author

Tofallis, C. / Multiple Neutral Regression. University of Hertfordshire, 2000. (Business School Working Papers). (Operational Research Paper).

Bibtex

@techreport{3122cf8995d442d6bd9f081ef24ec763,
title = "Multiple Neutral Regression",
abstract = "We present a multiple regression fitting method which, unlike least-squares regression, treats each variable in the same way. It can be used when seeking an empirical relationship between a number of variables for which data is available. It does not suffer from being scale-dependent - a disadvantage of orthogonal regression (total least squares). Thus changing the units of measurement will still lead to an equivalent model - this is clearly important if a model is to be meaningful. By formulating the estimation procedure as a fractional programming problem, we show that the optimal solution will be both global and unique.For the case of two variables the method has appeared under different names in different disciplines throughout the twentieth century- as the reduced major axis or line of organic correlation in biology, as Stromberg's impartial line in astronomy, and as diagonal regression in economics (in which field two Nobel laureates have published work on the method). We gather together the most important results already established.",
author = "C. Tofallis",
year = "2000",
language = "English",
series = "Business School Working Papers",
publisher = "University of Hertfordshire",
type = "WorkingPaper",
institution = "University of Hertfordshire",

}

RIS

TY - UNPB

T1 - Multiple Neutral Regression

AU - Tofallis, C.

PY - 2000

Y1 - 2000

N2 - We present a multiple regression fitting method which, unlike least-squares regression, treats each variable in the same way. It can be used when seeking an empirical relationship between a number of variables for which data is available. It does not suffer from being scale-dependent - a disadvantage of orthogonal regression (total least squares). Thus changing the units of measurement will still lead to an equivalent model - this is clearly important if a model is to be meaningful. By formulating the estimation procedure as a fractional programming problem, we show that the optimal solution will be both global and unique.For the case of two variables the method has appeared under different names in different disciplines throughout the twentieth century- as the reduced major axis or line of organic correlation in biology, as Stromberg's impartial line in astronomy, and as diagonal regression in economics (in which field two Nobel laureates have published work on the method). We gather together the most important results already established.

AB - We present a multiple regression fitting method which, unlike least-squares regression, treats each variable in the same way. It can be used when seeking an empirical relationship between a number of variables for which data is available. It does not suffer from being scale-dependent - a disadvantage of orthogonal regression (total least squares). Thus changing the units of measurement will still lead to an equivalent model - this is clearly important if a model is to be meaningful. By formulating the estimation procedure as a fractional programming problem, we show that the optimal solution will be both global and unique.For the case of two variables the method has appeared under different names in different disciplines throughout the twentieth century- as the reduced major axis or line of organic correlation in biology, as Stromberg's impartial line in astronomy, and as diagonal regression in economics (in which field two Nobel laureates have published work on the method). We gather together the most important results already established.

M3 - Working paper

T3 - Business School Working Papers

BT - Multiple Neutral Regression

PB - University of Hertfordshire

ER -