Assume the model:
X1 <- rnorm(1000)
X2 <- rnorm(1000)
B1 = 1.75 # known a-priorori
B2 = 0.5 # unknown a-priorori
Y <- 1.75 * X1 + 0.5 * X2 + rnorm(1000,sd=0.25)
Then wouldn't this do the trick? :
reg <- lm( (Y - 1.75 * X1) ~ X2 )
-Greg
> -----Original Message-----
> From: Rob Lee [mailto:rlee at fpcc.net]
> Sent: Thursday, October 03, 2002 3:15 PM
> To: r-help at stat.math.ethz.ch
> Subject: [R] lm fitting with a specified slope
>
>
>
> Is there an easy way to do a linear model with an a priori
> known slope?
>
> In essence, I want to minimize the residuals around a line of
> known slope.
>
> -R
>
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