[R] F-test where the coefficients in the H_0 is nonzero

[peter dalgaard]

This should do it:

> x <- rnorm(10)
> y <- x+rnorm(10)
> fit1 <- lm(y~x)
> fit2 <- lm(y~-1 + offset(0 + 1 * x))
> anova(fit2, fit1)
Analysis of Variance Table

Model 1: y ~ -1 + offset(0 + 1 * x)
Model 2: y ~ x
  Res.Df     RSS Df Sum of Sq      F Pr(>F)
1     10 10.6381                           
2      8  7.8096  2    2.8285 1.4487 0.2904


> On 2 Aug 2018, at 10:30 , John <miaojpm using gmail.com> wrote:
> 
> Hi,
> 
>   I try to run the regression
>   y = beta_0 + beta_1 x
>   and test H_0: (beta_0, beta_1) =(0,1) against H_1: H_0 is false
>   I believe I can run the regression
>   (y-x) = beta_0 +beta_1‘ x
>   and do the regular F-test (using lm functio) where the hypothesized
> coefficients are all zero.
> 
>   Is there any function in R that deal with the case where the
> coefficients are nonzero?
> 
> John
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

-- 
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd.mes using cbs.dk  Priv: PDalgd using gmail.com