Vertaile menetelmiä

	Ehtoyhdiste	OLS-regressio (Ordinary Least Squares)
Tieteenala	Ekonometria	Ekonometria
Menetelmäperhe	Regression model	Regression model
Syntyvuosi	1980	2019
Kehittäjä	Belsley, Kuh & Welsch	Wooldridge (textbook treatment); classical least squares
Tyyppi	Collinearity diagnostic index	Linear regression
Alkuperäislähde	Belsley, D. A., Kuh, E., & Welsch, R. E. (1980). Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. John Wiley & Sons. ISBN: 978-0-471-05856-4	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Rinnakkaisnimet	Belsley Condition Index, Collinearity Condition Index, Singular Value Condition Index, Koşul İndeksi	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Liittyvät	2	5
Tiivistelmä	The Condition Index, introduced by Belsley, Kuh, and Welsch (1980), is a scalar measure derived from singular value decomposition of the scaled regressor matrix. It quantifies the degree of near-linear dependence among predictors in ordinary least squares regression, enabling analysts to detect collinearity that inflates coefficient variance and destabilises parameter estimates. Widely used in economics, social sciences, and biomedical research wherever OLS regression is applied.	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).