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  2. Variance inflation factor - Wikipedia

    en.wikipedia.org/wiki/Variance_inflation_factor

    The VIF provides an index that measures how much the variance (the square of the estimate's standard deviation) of an estimated regression coefficient is increased because of collinearity. Cuthbert Daniel claims to have invented the concept behind the variance inflation factor, but did not come up with the name. [2]

  3. Vif - Wikipedia

    en.wikipedia.org/wiki/Vif

    Variance inflation factor, a measure of collinearity in statistical regression models; Visual information fidelity, measure for image quality assessment; Value of in-force, a life insurance term "Virtual Interface", a networking term; Viral infectivity factor of retroviruses, specifically used in the context of HIV "Vector Unit InterFace" on ...

  4. Multicollinearity - Wikipedia

    en.wikipedia.org/wiki/Multicollinearity

    Variance inflation factors are often misused as criteria in stepwise regression (i.e. for variable inclusion/exclusion), a use that "lacks any logical basis but also is fundamentally misleading as a rule-of-thumb".

  5. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    The design effect is a positive real number that indicates an inflation ... Variance of an estimator ^ ... , proposed by Kish in 1995, is the Design Effect Factor ...

  6. Talk:Variance inflation factor - Wikipedia

    en.wikipedia.org/wiki/Talk:Variance_inflation_factor

    The upper limit of 10 for an acceptable VIF is suggested by Samprit Chatterjee and Bertram Price in their book Regression Analysis by Example, 2nd ed, 1991, John Wiley & Sons, Inc.

  7. Regression dilution - Wikipedia

    en.wikipedia.org/wiki/Regression_dilution

    The greater the variance in the x measurement, the closer the estimated slope must approach zero instead of the true value. Suppose the green and blue data points capture the same data, but with errors (either +1 or -1 on x-axis) for the green points.

  8. Autoregressive conditional heteroskedasticity - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_conditional...

    where , , > and (+ ) + <, which ensures the non-negativity and stationarity of the variance process. For stock returns, parameter θ {\displaystyle ~\theta } is usually estimated to be positive; in this case, it reflects a phenomenon commonly referred to as the "leverage effect", signifying that negative returns increase future volatility by a ...

  9. Category:Statistical ratios - Wikipedia

    en.wikipedia.org/wiki/Category:Statistical_ratios

    This page was last edited on 13 September 2019, at 22:25 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.