Gota Morota
1/19/16
One locus to the infinitesimal model - 1
Assumptions:
\[ \begin{align*} y_i &= u_i + e_i \\ y_i &= W_{i1}a_1 + W_{i2}a_2 + \cdots W_{ik}a_k + e_i \end{align*} \] Variance of \( \mathbf{u} \) is \[ \begin{align*} Var(\mathbf{u}) &= \sum^K_{k=1} Var(W_k a_k) \\ &= \sum^K_{k=1} Var(W_k) a_k^2 \\ &= \sum^K_{k=1} 2p_k(1-p_k) a_k^2 \end{align*} \]
Assumptions:
Assumptions:
\[ \begin{align*} h^2_g &= \frac{\sum^K_{k=1}2p_k(1-p_k) a_k^2 }{\sum^K_{k=1}2p_k(1-p_k) a_k^2 + \sigma^2_e} \end{align*} \] Assumptions:
\[ \begin{align*} h^2_g &= \frac{\sum^K_{k=1} 2p_k(1-p_k) a_k^2 + 2 \sum^K_{k=1}\sum^{K}_{l=k+1} 2 \rho_{kl} \sqrt{p_k(1-p_k)p_l(1 - p_l)} a_k a_l }{\sum^K_{k=1} 2p_k(1-p_k) a_k^2 + 2 \sum^K_{k=1}\sum^{K}_{l=k+1} 2 \rho_{kl} \sqrt{p_k(1-p_k)p_l(1 - p_l)} a_k a_l + \sigma^2_e} \end{align*} \]