Variance Inflation Factor VIC() with a matrix

Dear Martin,
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of Martin H. Schmidt
Sent: Thursday, September 20, 2012 8:52 AM
To: r-help at r-project.org
Subject: [R] Variance Inflation Factor VIC() with a matrix

Hi everyone,

Running the vif() function from the car package like

----------------------------------------------------
 > reg2 <- lm(CARsPur~Delay_max10+LawChange+MarketTrend_20d+MultiTrade,
data=data.frame(VarVecPur))
 > vif(reg2)
     Delay_max10       LawChange MarketTrend_20d      MultiTrade
        1.010572        1.009874        1.004278        1.003351
----------------------------------------------------

gives a useful result. But using the right-hand variables as a matrix in
the following way doesn't work with the vif() function:

----------------------------------------------------
 > reg  <- lm(CARsPur~VarVecPur)
 > summary(reg)
Call:
lm(formula = CARsPur ~ VarVecPur)

Residuals:
      Min       1Q   Median       3Q      Max
-0.72885 -0.06461  0.00493  0.06873  0.74936

Coefficients:
                           Estimate Std. Error t value Pr(>|t|)
(Intercept)              -0.037860   0.006175  -6.131 9.25e-10 ***
VarVecPurDelay_max10      0.003661   0.001593   2.298   0.0216 *
VarVecPurLawChange        0.004679   0.006185   0.757   0.4493
VarVecPurMarketTrend_20d  0.019015   0.001409  13.493  < 2e-16 ***
VarVecPurMultiTrade      -0.005081   0.003129  -1.624   0.1045
---
Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1

Residual standard error: 0.1229 on 6272 degrees of freedom
Multiple R-squared: 0.03021,    Adjusted R-squared: 0.02959
F-statistic: 48.84 on 4 and 6272 DF,  p-value: < 2.2e-16

 > vif(reg)
Error in vif.lm(reg) : model contains fewer than 2 terms

----------------------------------------------------
Is there a solution or a way to work around?
Not with vif() in the car package, which wants to compute generalized variance inflation factors (GVIFs) for multi-df terms in the model. Single-df VIFs are pretty simple, so you could just write your own function. Alternatively, there are other packages on CRAN, such as DAAG, that compute VIFs, so you might try one of these.

I hope this helps,
 John

-----------------------------------------------
John Fox
Senator McMaster Professor of Social Statistics
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
Thank you very much in advanced.

--
Kind Regards,

Martin H. Schmidt
Humboldt University Berlin

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Variance Inflation Factor VIC() with a matrix

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