1. The bivariate normal density can be written as $$N(x, y) = frac{1}{2pisigma_xsigma_ysqrt{1-ho^2}}$$ $$times expleft[-frac{1}{2(1-ho^2)}left[left(frac{x-mu_x}{sigma_x} ight)^2 - 2holeft(frac{x-mu_x}{sigma_x} ight)left(frac{y-mu_y}{sigma_y} ight) + left(frac{y-mu_y}{sigma_y} ight)^2 ight] ight]$$

1. The bivariate normal density can be written as

$$N(x, y) = \frac{1}{2\pi\sigma_x\sigma_y\sqrt{1-ho^2}}$$

$$\times exp\left[-\frac{1}{2(1-ho^2)}\left[\left(\frac{x-\mu_x}{\sigma_x}\right)^2 - 2ho\left(\frac{x-\mu_x}{\sigma_x}\right)\left(\frac{y-\mu_y}{\sigma_y}\right) + \left(\frac{y-\mu_y}{\sigma_y}\right)^2\right]\right]$$

where |p| < 1, 0, < 0, 0, > 0.

Put this in the form of Eq. (10.3.1a) by identifying R,

c, x, and K.