FIT OF THE ASSAY DATA BY GLS 
WITH POWER VARIANCE, THETA UNKNOWN AND ESTIMATED BY
      PL 
 
 
OLS estimate  482.553 6222.278 2.195828 1.155375 
 
Estimate of assumed constant SD of y  100.7284 
 
 
Iteration  1 
Estimate of theta  0.4245 
 
Iteration  1 
GLS estimate of beta  580.4788 6194.05 2.168291 1.212388 
 
Iteration  2 
Estimate of theta  0.6637 
 
Iteration  2 
GLS estimate of beta  605.9669 6183.403 2.163719 1.232371 
 
Iteration  3 
Estimate of theta  0.7034 
 
Iteration  3 
GLS estimate of beta  608.8951 6182.221 2.163208 1.234824 
 
Iteration  4 
Estimate of theta  0.7072 
 
Iteration  4 
GLS estimate of beta  609.1568 6182.124 2.163157 1.235043 
 
Iteration  5 
Estimate of theta  0.7075 
 
Iteration  5 
GLS estimate of beta  609.1797 6182.115 2.163153 1.235062 
 
Iteration  6 
Estimate of theta  0.7075 
 
Iteration  6 
GLS estimate of beta  609.1817 6182.115 2.163152 1.235063 
 
Iteration  7 
Estimate of theta  0.7075 
 
Iteration  7 
GLS estimate of beta  609.1818 6182.115 2.163152 1.235063 
 
Iteration  8 
Estimate of theta  0.7075 
 
Iteration  8 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  9 
Estimate of theta  0.7075 
 
Iteration  9 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  10 
Estimate of theta  0.7075 
 
Iteration  10 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  11 
Estimate of theta  0.7075 
 
Iteration  11 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  12 
Estimate of theta  0.7075 
 
Iteration  12 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  13 
Estimate of theta  0.7075 
 
Iteration  13 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  14 
Estimate of theta  0.7075 
 
Iteration  14 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  15 
Estimate of theta  0.7075 
 
Iteration  15 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  16 
Estimate of theta  0.7075 
 
Iteration  16 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  17 
Estimate of theta  0.7075 
 
Iteration  17 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  18 
Estimate of theta  0.7075 
 
Iteration  18 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  19 
Estimate of theta  0.7075 
 
Iteration  19 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Iteration  20 
Estimate of theta  0.7075 
 
Iteration  20 
GLS estimate of beta  609.1819 6182.115 2.163152 1.235063 
 
Final estimate of sigma  0.306163 
 
Final estimate of theta  0.707522 
 

Formula: ywt ~ weightfunc(x, b1, b2, b3, b4, wt)

Parameters:
    Estimate Std. Error t value Pr(>|t|)    
b1 6.092e+02  4.660e+01   13.07 2.22e-14 ***
b2 6.182e+03  5.321e+01  116.18  < 2e-16 ***
b3 2.163e+00  2.814e-02   76.88  < 2e-16 ***
b4 1.235e+00  4.236e-02   29.16  < 2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 0.3062 on 32 degrees of freedom

Number of iterations to convergence: 6 
Achieved convergence tolerance: 6.142e-06