stepAIC invalid scope argument

You are right, it works fine with a different name. Its a bad habit that
I need to shake off.

The error message said that the second argument was invalid. The second
argument in stepAIC and addterm is 'scope' and thus the title.

Thank you again.

Regards, Adai



On Mon, 2005-08-15 at 15:23 +0100, Prof Brian Ripley wrote:

Try not to use the name of an R object ... the error is caused by using
'df' as the second argument to eval().

It works with DF in place of df.

I don;t understand your subject line: that is not the error message you
received.

On Mon, 15 Aug 2005, Adaikalavan Ramasamy wrote:

I am trying to replicate the first example from stepAIC from the MASS
package with my own dataset but am running into error. If someone can
point where I have gone wrong, I would appreciate it very much.

Here is an example :

set.seed(1)
df   <- data.frame( x1=rnorm(1000), x2=rnorm(1000), x3=rnorm(1000) )
df$y <- 0.5*df$x1 + rnorm(1000, mean=8, sd=0.5)
# pairs(df); head(df)

lo  <- aov( y ~ 1, data=df )
hi  <- aov( y ~ .^2, data=df )
mid <- aov( y ~ x2 + x3, data=df )

Running any of the following commands

stepAIC( mid, scope=list(upper = ~x1 + x2 + x3 , lower = ~1) )
stepAIC( mid, scope=list(upper = hi , lower = lo) )
addterm( mid, ~ x1 + x2 + x3 )
addterm( lo, hi )

gives the same error message :
 Error in eval(expr, envir, enclos) : invalid second argument

Here is a traceback of the first failed command :
14: eval(predvars, data, env)
13: model.frame.default(formula = y ~ x2 + x3 + x1, data = df, drop.unused.levels = TRUE)
12: model.frame(formula = y ~ x2 + x3 + x1, data = df, drop.unused.levels = TRUE)
11: eval(expr, envir, enclos)
10: eval(mf, parent.frame())
9: lm(formula = y ~ x2 + x3 + x1, data = df, method = "model.frame")
8: eval(expr, envir, enclos)
7: eval(fcall, env, parent.frame())
6: model.frame.lm(fob, xlev = object$xlevels)
5: model.frame(fob, xlev = object$xlevels)
4: stats:::add1.lm(object, scope = scope, scale = scale)
3: addterm.lm(fit, scope$add, scale = scale, trace = max(0, trace - 1), k = k, ...)
2: addterm(fit, scope$add, scale = scale, trace = max(0, trace - 1), k = k, ...)
1: stepAIC(mid, scope = list(upper = ~x1 + x2 + x3, lower = ~1))

Any pointers would be much appreciated. Thank you.

Regards, Adai