> Specifically my model has one response and two predictors, i.e. it's of the
> form
>
> Y = b_0+b_1*X_1+b_2*X_2
>
> Plotting the regression line for a single predictor model
>
> Y = b_0+b_1*X_1
>
> is simple enough, just call abline() with the coefficients returned by lm().

## Advertising

Single variable linear model has only 1 regression line.
For two predictors, your regression line! is a surface. (it is not a line
anymore)
For 3 predictors, your regression line! is a volume etcâ€¦
>
> However, I don't know if this can be adapted to multivariable linear models.
Yes, but in a limited manner. Assume your model is Y ~ x1 + x2 + x3
set x2 and x3 constant (for instance, to median of the series) predict
(predict.lm) Y.predicted values against x1. Order x1 and Y.predicted values
and plot them by lines command on Y ~ x1 scatter plot.
Do same thing for other variables.
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