Elegant way to express residual calculation in R?

    Hi All,

    I am illustrating a simple, two-way ANOVA using the 
following data and I'm 
    having difficulty in expressing the predicted values 
succinctly in R.

    X<- data.frame(read.table(textConnection("
        Machine.1    Machine.2    Machine.3
        53           61           51
        47           55           51
        46           52           49
        50           58           54
        49           54           50"
    ), header=TRUE))
    rownames(X)<- paste("Operator.", 1:nrow(X), sep="")
    print(X)

    # I'd like to know if there is a more elegant way to 
calculate the residuals
    # than the following, which seems to be rather a kludge. 
If you care to read
    # the code you'll see what I mean. 

    machine.adjustment<-  colMeans(X) - mean(mean(X))    # 
length(machine.adjustment)==3
    operator.adjustment<- rowMeans(X) - mean(mean(X))    # 
length(operator.adjustment)==5
    X.predicted<- numeric(0)
    for (j in 1:ncol(X))
    {
        new.col<- mean(mean(X)) + operator.adjustment + 
machine.adjustment[j]
        X.predicted<- cbind(X.predicted, new.col)
    }
    print(X.predicted)
    X.residual<- X - X.predicted
    SS.E<- sum( X.residual^2 )

It seems like there ought to be some way of doing that a 
little bit cleaner ...

Thanks,

Jack.

		
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