# [R] ANOVA(L, Terms...)

Francisco J. Zagmutt Vergara fzagmutt at hotmail.com
Tue Sep 23 03:19:26 CEST 2003

Hi There

I have a lm object with 4 parameters and I want to test wether 2 parameters
are equal using a Wald test (basically b1=b2 or b1-b2 =0).  In the help file
from R it says that under ANOVA the optional arguments " Terms" or "L" test
whether a linear combination is equal to 0.  I tried;

>anova(m1, Terms = Beta1-Beta2=0) but I get the error:
Object " Beta1" must be assigned locally before replacement.

I also tried

>anova (m1, Terms = 1-2 = 0) and I get:

Invalid assginment: No object name : 1-2 = 0

What am I doing wrong?

>From: Jean Eid <jeaneid at chass.utoronto.ca>
>To: r-help at stat.math.ethz.ch
>Subject: Re: [R] ksmooth in  SPLUS vs R Date: Mon, 22 Sep 2003 20:23:32
>-0400
>
>Please do forget my questions as they are really trivial and I do not kno
>what I was thinking of.
>
>Thank you thomas for clarifying my cloudy head today.
>
>jean,
>
>
>On Mon, 22 Sep 2003, Jean Eid wrote:
>
> > I am working with a model that I have to estimate a nonparametric
> > function. The model is partial linear i.e.
> >
> > Y=X$\beta$ + f(z) + $\epsilon$
> >
> > I am using the ' double residual methods' Robinson (1988) Speckman
>(1988)
> > where I estimate a nonparametric function for each of the parametric
> > variables in terms of the nonparametric one i.e.
> >
> > X[,i]=g(Z)+ u
> >
> > this is done because I need the $E( X[,i]\vert Z)$ for each position j
>in
> > the vectors.
> >
> > the problem is that when I use the ksmooth() function in R it estimates
> > the function at different points and not those that consist of the Z
> > vector.
> >
> > the ksmooth() function in Splus on the other hand evaluates the points
>at
> > the corresponding Z vector. both codes are given below
> >
> >
> > d<-ksmooth(lprice,XX[,i],kernel="box")
> > unique(lprice-d\$x)
> >
> > in SPLUS will generate 0 while in R it generates a vector of different
> > values.
> >
> >
> >
> > My second question is regarding the sm library:
> >
> > d<-sm.regression(lprice, XX[,i], h=sd(lprice), display="none")
> > will only generate 50 point estimates while  NROW(XX[,i]) = 3897
> > and when I do
> > d<-sm.regression(lprice, XX[,i], h=sd(lprice), display="none",
> > ngrid=NROW(lprice))
> >
> > I get the right dimension of the estimated points but again they are not
> > estimated at the points in lprice.
> >
> >
> > Any help is greatly appreciated.
> >
> > P.S. I have Bowman and Azzalini book but unfortunately it does not
>clarify
> > the procedures in sm.regression()
> >
> > Jean,
> >
> > ______________________________________________
> > R-help at stat.math.ethz.ch mailing list
> > https://www.stat.math.ethz.ch/mailman/listinfo/r-help
> >
>
>______________________________________________
>R-help at stat.math.ethz.ch mailing list
>https://www.stat.math.ethz.ch/mailman/listinfo/r-help

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