Why predicted polynomial changes drastically when only the resolution of prediction grid changes?

Question

Why I have the exact same model, but run predictions on different grid size (by 0.001 vs by 0.01) getting different predictions?

set.seed(0)         


        

Answer 1

In the first place, the predict lines don't fit the original data. You failed to make poly objs for prediction.

...
poly_ori <- poly(x, poly_df)    # important
...   

plot(x,y)

x_plt1 = seq(-1, 1, 0.001)
x_plt_exp1 = as.data.frame(poly(x_plt1, poly_df, coefs = attr(poly_ori, "coefs")))
lines(x_plt1, predict(fit, x_plt_exp1),lwd = 3, col = 2)

x_plt2 = seq(-1, 1, 0.01)
x_plt_exp2 = as.data.frame(poly(x_plt2, poly_df, coefs = attr(poly_ori, "coefs")))
lines(x_plt2, predict(fit, x_plt_exp2), lwd = 3, col = 3)