Constructing a lm for predict() by hand

One relatively easy way would be to construct some dummy data with the 
appropriate names and formula, use lm() to construct the model object, and 
then change the coefficients in the model object to be what you want (e.g., 
by fit$coefficients[2] <- 0.79).  This should then work with 
predict().  Don't make the mistake of thinking that output than output from 
anything other than predict(obj, newdata=data) will mean anything sensible 
-- summary(), predict(, se=T), ...

If your data is all numeric, then the easiest way might be just to use 
matrix computations:

pred <- cbind(1, data) %*% coef

where data is n x k matrix, coef is a vector of length k+1, and the 
intercept is the first element of coef.

hope this helps,

Tony Plate

Constructing a lm for predict() by hand

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