这是一份多元统计分析作业代写的成功案

Providing the breeders’ equation holds over several generations, the cumulative response to $m$ generations of selection is just
$$
R^{(m)}=\sum_{t=1}^{m} R(t)=\sum_{t=1}^{m} \mathbf{G}(t) \beta(t) .
$$
In particular, if the genetic covariance matrix remains constant, then
$$
R^{(m)}=\mathbf{G}\left(\sum_{t=1}^{m} \beta(t)\right)
$$Hence, if we observe a total response to selection of $\mathbf{R}{\text {total }}$, then we can estimate the cumulative selection differential as $$ \beta{\text {wotal }}=\sum \beta(t)=\mathbf{G}^{-1} \mathbf{R}_{\text {wotal }} \text {. }
$$

MA3066/STAT 505/STAT 530/EXST 7037/STAT 450/550/STA3200/MATH5855 COURSE NOTES ：

If one has access to a sample of generation means (as opposed to a starting and end points), then notes that a more powerful test can be obtained (from the theory of random walks) by considering $\Delta \mu^{}$, the largest absolute deviation from the starting mean anywhere along the series of $t$ generation means. Here, the rate of evolution is too fast for drift if $$ \sigma_{m}^{2}<\frac{\left(\Delta \mu^{}\right)^{2}}{2 t(2.50)^{2}}=0.080 \frac{\left(\Delta \mu^{}\right)^{2}}{t} $$ while it is too slow for drift when $$ \sigma_{m}^{2}>\frac{\left(\Delta \mu^{}\right)^{2}}{2 t(0.56)^{2}}=1.59 \frac{\left(\Delta \mu^{*}\right)^{2}}{t} .
$$
Note by comparison with that the tests for too fast a divergence are very similar, while Bookstein’s test for too slow a divergence (a potential signature of stabilizing selection) is much less stringent than the Turelli-Gillespie-Lande test.