[R] Bad points in regression

[Alberto Monteiro]

Ted Harding wrote:
> 
>> alpha <- 0.3
>> beta <- 0.4
>> sigma <- 0.5
>> err <- rnorm(100)
>> err[15] <- 5; err[25] <- -4; err[50] <- 10
>> x <- 1:100
>> y <- alpha + beta * x + sigma * err
>> ll <- lm(y ~ x)
>> plot(ll)
> 
> ll is the output of a linear model fiited by lm(), and so has
> several components (see ?lm in the section "Value"), one of
> which is "residuals" (which can be abbreviated to "res").
> 
> So, in the case of your example,
> 
>   which(abs(ll$res)>2)
>   15 25 50
> 
> extracts the information you want (and the ">2" was inspired by
> looking at the "residuals" plot from your "plot(ll)").
>
Ok, but how can I grab those points _in general_? What is the
criterium that plot used to mark those points as bad points?

names(ll)

gives:

 [1] "coefficients"  "residuals"     "effects"       "rank"         
 [5] "fitted.values" "assign"        "qr"            "df.residual"  
 [9] "xlevels"       "call"          "terms"         "model"        

None of them include information about those bad points.

Alberto Monteiro