> > x wrote:
> > > x2 NA 1.797e+14 NA NA
> > > x2' NA 6.475e+14 NA
> NA
> > >
> > > Residual standard error: 82.44 on 95 degrees of
> > freedom
> > > Adjusted R-Squared: 0.9992
> > > Error in if (coef[i] > 0 & (i > 2 |
> coef[1]
> > != 0 | Intc != 0)) "+" else NULL : missing
> value
> > where TRUE/FALSE needed
>
> > It just appears that you have perfect prediction, so
> you
> > have quite an unusual dataset to be doing inference
> on.
> >
> > Frank
>
> OK, I tried different test datasets.
>
> 1) y1 <- rnorm(1000); x1 <- runif(1000); x2 <-
> runif(1000);
> does NOT show any error.
>
> 2) y1 = 10*x1*e1 + 10*x2*e1 + 100*e1 where x1=1..100,
> x2=100..1, e1=Gaussian noise
> gives me error like before.
>
> 3) y1 = x1^3*e1 + x2^3*e1 + 100*e1^2 also gives me the same
> error.
>
> Now, why should there be perfect prediction in cases 2
> & 3?
I tried another test - I replicated x1 to be x2 as well. While y1~rcs(x1,3)
works y1~( rcs(x1,3) + rcs(x2,3) ) does not (error message shown above).
Thanks again,
sp