FIT OF THE SKIN CANCER DATA BY GLS OLS estimate 0.385539 0.433959 0.180282 0.003334 0.306852 0.314332 Iteration 1 GLS estimate of beta 0.329136 0.429595 0.204387 0.004628 0.288417 0.289038 Iteration 2 GLS estimate of beta 0.319993 0.429924 0.202162 0.004733 0.292014 0.290063 Iteration 3 GLS estimate of beta 0.318727 0.429916 0.202452 0.004755 0.291845 0.289866 Iteration 4 GLS estimate of beta 0.318554 0.429918 0.202426 0.004758 0.291887 0.289875 Iteration 5 GLS estimate of beta 0.31853 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 6 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 7 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 8 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 9 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 10 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 11 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 12 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 13 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 14 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 15 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 16 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 17 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 18 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 19 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 20 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 21 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 22 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 23 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 24 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 25 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 26 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 27 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 28 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 29 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 30 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 31 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 32 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 33 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 34 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 35 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 36 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 37 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 38 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 39 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 40 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 41 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 42 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 43 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 44 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 45 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 46 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 47 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 48 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 49 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Iteration 50 GLS estimate of beta 0.318527 0.429918 0.202429 0.004758 0.291886 0.289872 Formula: ywt ~ weightfunc(x, b1, b2, b3, b4, b5, b6, wt) Parameters: Estimate Std. Error t value Pr(>|t|) b1 0.318527 0.273824 1.163 0.245019 b2 0.429918 0.084172 5.108 3.94e-07 *** b3 0.202429 0.093544 2.164 0.030714 * b4 0.004758 0.004054 1.174 0.240806 b5 0.291886 0.072322 4.036 5.88e-05 *** b6 0.289872 0.084807 3.418 0.000658 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 1.986 on 948 degrees of freedom Number of iterations to convergence: 7 Achieved convergence tolerance: 2.738e-09