例09-15计算结果.lst

SAS应用_医学统计学的例题程序及其结果,学习SAS的必备资料.

                                       The SAS System         09:34 Monday, April 1, 2002  81

 Non-Linear Least Squares Iterative Phase     Dependent Variable Y       Method: Gauss-Newton
                     Iter       A              B        Sum of Squares
                        0       4.000000       0.030000         496541
                        1       3.437978       0.022758   65620.799712
                        2       3.394837       0.006838    9535.464658
                        3       3.804354      -0.016482    1267.305221
                        4       4.015841      -0.032849     122.168744
                        5       4.064593      -0.038780      50.351969
                        6       4.070521      -0.039552      49.460823
                        7       4.070835      -0.039585      49.459302
                        8       4.070846      -0.039586      49.459300
                        9       4.070847      -0.039586      49.459300
NOTE: Convergence criterion met.


             Non-Linear Least Squares Summary Statistics     Dependent Variable Y

               Source                DF Sum of Squares     Mean Square

               Regression             2   12060.540700     6030.270350
               Residual              13      49.459300        3.804562
               Uncorrected Total     15   12110.000000

               (Corrected Total)     14    3943.333333


               Parameter     Estimate    Asymptotic             Asymptotic 95 %
                                         Std. Error         Confidence Interval
                                                            Lower         Upper
               A          4.070846731 0.02511937531  4.0165796521  4.1251138093
               B         -0.039586452 0.00171129396 -0.0432834752 -0.0358894280


                                Asymptotic Correlation Matrix

                          Corr                 A                 B
                          ----------------------------------------
                          A                    1      -0.707147352
                          B         -0.707147352                 1