Alireza,
The "lm" function fits the linear regression (linear model), the
"predict" function predicts new response values based on values of the
predictor variables.
Try something like:
> mydata <- data.frame( x=1:30, y=31:60+rnorm(30) )
> fit1 <- lm( y ~ x, data=mydata )
> summary(fit1) # optional
> plot(fit1) # optional
> newdata <- data.frame(x=3.5)
> predict(fit1, newdata)
Also you should reread section 11 of "An Introduction to R" to get
more detail.
Hope this helps,
--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Dr. Alireza Zolfaghari
> Sent: Wednesday, November 12, 2008 1:57 PM
> To: R-help
> Subject: [R] Linear regression
>
> Hi List,
> Does anybody know what function I need to use for a simple regression?
>
> Here is the data: I want to find the value for x1=3.5
> data<-data.frame(x=c(1:30),Value=c(31:60))
> x1<-3.5
>
> Regards,
> Alireza
>
> [[alternative HTML version deleted]]
>
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