[R] predict.lm with missing data

[Vadim Ogranovich]

Dear R-Users,

Say I have a data frame 'data' with missing values and I fit
> data.lm <- lm(y~x, data=data, na.action=na.omit)

Now I want to compute predictions for each observation of 'data' (having NA
where the data was missing).

The straightforward predict(data.lm) is not good since it produces a vector
that is shorter than the number of rows in data (because of the missings).

Does anyone know how to do this?

Thanks, Vadim

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