Loading required package: methods

Call:
lmrob(formula = y ~ 1 + x + I(x^2))

Weighted Residuals:
      Min        1Q    Median        3Q       Max
 -18.8749   -2.4062    0.3484    2.0479 1729.0771

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  5.59400    0.09314   60.06   <2e-16 ***
x            4.89557    0.10039   48.77   <2e-16 ***
I(x^2)      -0.48338    0.02451  -19.72   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Robust residual standard error: 3.08
Convergence in 13 IRWLS iterations

Robustness weights:
 61 observations c(13,16,23,26,27,47,59,60,69,79,92,98,105,115,123,124,127,137,139,150,159,170,177,179,187,195,205,224,230,238,239,242,249,261,265,266,270,298,312,317,328,336,339,362,370,380,386,399,420,427,438,442,447,450,461,463,464,470,483,3755,5530)
     are outliers with |weight| = 0 ( < 1.2e-05);
 229 weights are ~= 1. The remaining 8254 ones are summarized as
     Min.   1st Qu.    Median      Mean   3rd Qu.      Max.
0.0007646 0.8666000 0.9477000 0.9060000 0.9903000 0.9990000
Algorithmic parameters:
tuning.chi         bb tuning.psi refine.tol    rel.tol
 1.5476400  0.5000000  4.6850610  0.0000001  0.0000001
 nResample     max.it     groups    n.group   best.r.s   k.fast.s      k.max
       500         50          5        400          2          1        200
 trace.lev compute.rd  numpoints
         0          0         10
          psi        method           cov
   "bisquare"          "MM" ".vcov.avar1"
seed : int(0)