[R-SIG-Finance] [R] Statistically significant in linear and non-linear model

[Hsiao-nan Cheung]

Perhaps I should.... Now the example.

Maybe I could specify my question more clearly. For example, a linear model is y = alpha + beta*x + epsilon, and this beta is not statistically significant. Then a non-linear model, e.g., y = eta + gamma*exp(x) + omega, since exp(x) = 1 + x + (x^2)/(2!) + (x^3)/(3!) + ..., then y = eta + gamma*(1+x+x^2/2+...) + omega. But beta in the former formula is not statistically significant, is there probability that gamma is statistically significant?

HC

> -----Original Message-----
> From: markleeds at verizon.net [mailto:markleeds at verizon.net]
> Sent: 2008年10月8日 1:56
> To: Hsiao-nan Cheung
> Subject: RE: [R] Statistically significant in linear and non-linear
> model
> 
>   you might be better off sending the example you sent me with gamma
> and
> beta ? it's just a thought ?
> 
> 
> 
> On Tue, Oct 7, 2008 at  1:46 PM, Hsiao-nan Cheung wrote:
> 
> > Hi,
> >
> >
> > I have a question to ask. if in a linear regression model, the
> > independent
> > variables are not statistically significant, is it necessary to test
> > these
> > variables in a non-linear model? Since most of non-linear form of a
> > variable
> > can be represented to a linear combination using Taylor's theorem, so
> > I
> > wonder whether the non-linear form is also not statistically
> > significant in
> > such a situation.
> >
> >
> > Best Regards
> >
> > Hsiao-nan Cheung
> >
> > 2008/10/08
> >
> >
> >
> >
> >
> > 	[[alternative HTML version deleted]]
> >
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