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Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Kielelezo cha Kupanda kwa Tofauti (VIF)×Kielelezo cha Hali×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili19701980
MwanzilishiDonald MarquardtBelsley, Kuh & Welsch
AinaDiagnostic statisticCollinearity diagnostic index
Chanzo asiliaMarquardt, D. W. (1970). Generalized inverses, ridge regression, biased linear estimation, and nonlinear estimation. Technometrics, 12(3), 591–612. DOI ↗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
Majina mbadalaVIF, Variance Inflation Index, Multicollinearity Inflation Factor, Varyans Enflasyon FaktörüBelsley Condition Index, Collinearity Condition Index, Singular Value Condition Index, Koşul İndeksi
Zinazohusiana32
MuhtasariThe Variance Inflation Factor (VIF) is a scalar diagnostic statistic proposed by Donald Marquardt (1970) that quantifies how much the variance of an estimated regression coefficient increases due to linear dependence—multicollinearity—among the predictors in an ordinary least squares model. It is routinely applied in econometrics, social science, and biomedical research whenever analysts suspect that two or more independent variables move together closely enough to destabilize coefficient estimates.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.
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ScholarGateLinganisha mbinu: Variance Inflation Factor · Condition Index. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare