Page 290 - Linear Models for the Prediction of Animal Breeding Values 3rd Edition
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Rounds of iteration
         Effects  0 a   1      2      3      4     16    17     18     19     20

         b      4.333  4.333  4.381  4.370  4.368  4.358  4.358  4.358  4.358  4.358
          1
         b      3.400  3.400  3.433  3.365  3.414  3.404  3.404  3.404  3.404  3.404
          2
         u ˆ    0.000  0.267  0.164  0.185  0.131  0.099  0.099  0.099  0.099  0.099
          1
         u ˆ    0.000  0.000 −0.073 −0.003 −0.039 −0.018 −0.018 −0.018 −0.018 −0.018
          2
         u ˆ    0.000 −0.033 −0.080 −0.049 −0.070 −0.041 −0.041 −0.041 −0.041 −0.041
          3
         u ˆ    0.167 −0.138 −0.007 −0.035  0.000 −0.008 −0.008 −0.008 −0.008 −0.008
          4
         u ˆ   −0.500 −0.411 −0.248 −0.265 −0.204 −0.185 −0.185 −0.185 −0.185 −0.185
          5
         u ˆ    0.500  0.345  0.318  0.237  0.236  0.178  0.178  0.178  0.177  0.177
          6
         u ˆ   −0.833 −0.406 −0.390 −0.301 −0.295 −0.249 −0.249 −0.249 −0.249 −0.249
          7
         u ˆ    0.667  0.400  0.286  0.232  0.207  0.183  0.183  0.183  0.183  0.183
          8
         CONV   1.000  2.3 −2  3.9 −3  1.4 −3  5.9 −4  4.2 −8  1.6 −8  1.0 −8  4.1 −9  3.0 −9
         a Starting values.
            The starting solutions for sex effect were the mean yield for each sex subclass
         and, for animals with records, starting solutions were the deviation of their yields
         from the mean yield of their respective sex subclass and zero for ancestors. The final
         solutions obtained after the 20th round of iteration were exactly the same as obtained
         in Section 3.2 by direct inversion of the coefficient matrix. The solutions for sex effect
         were obtained using Eqn 17.2. Thus in the first round of iteration the solution for
         males was:
                 1 ⎛  m                    ⎞
             1 b =  c ⎜ ∑ 1 y − (1)u −  7 ˆ  (1)  8 u ˆ  ⎟ ⎠
                              4 (1)u −
                             ˆ
                 11 ⎝
                       k
                    k=
         where c  is the diagonal element of the coefficient matrix for level i of sex effect and
               ii
         m is the number of records for males.
            b  = 1/3(13.0 − 0.167 − (−0.833) − 0.667) = 4.333
             1
         However, using Eqn 17.2 to obtain animal solutions caused the system of equations
         to diverge. A relaxation factor (w) of 0.8 was therefore employed and solutions for
         animal j were computed as:
                   ⎛ ⎡  1 ⎞ ⎛              ⎞     ⎤
                                         r 1−
             r
            ˆ u = w ⎢    y −  cb ˆ r 1−  − ∑  c lt k ⎟  −  ˆ u r 1−  r −1
                                        ˆ u
                                               j ⎥ + ˆ u
             j     ⎜ c ⎟ ⎜  j  li i                  j
                  ⎣ ⎝ ⎢  ll ⎠ ⎝     k      ⎠     ⎦ ⎦ ⎥
         where l = j + n, t = k + n, with n = 2; the total number of levels of fixed effect, c  and c ,
                                                                           lt   li
         for instance, are the elements of the coefficient matrix between animals j and k, and
         animal j and level i of sex effect, respectively. Thus in the first round of iteration,
         solutions for animals 1 and 8 are calculated as:
             1
                                                        0
            u  = w[{1/c (y  − (1)uˆ  − (−1.333)uˆ  − (−2)uˆ )} − uˆ ] + uˆ 0
             ˆ
             1        33  1    2           4      6     1    1
               = w[{1/3.667(0 − 0 − (−0.223) − (−1))} − 0] + 0
               = 0.8(0.334 − 0) + 0 = 0.267
         and:
                                                     0
             1
            u  = w[{1/c  (y  − (1)b  − (−2)u  − (−2)u )} − u ] + u ˆ 0
                                               ˆ
                                                     ˆ
             ˆ
                                        ˆ
             8        1010  8    1      3       6    8    8
               = w[{1/5(5 − 4.333 − 0 − (−1))} − 0.667] + 0.667
               = 0.8(0.333 − 0.667) + 0.667 = 0.400
          274                                                            Chapter 17
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