1. The bivariate normal density can be written as $$N(x, y) = frac{1}{2pisigma_xsigma_ysqrt{1-ho^2}}$$ $$times expleft[-frac{1}{2(1-ho^2)}left[left(frac{x-mu_x}{sigma_x} ight)^2 -...
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1. The bivariate normal density can be written as
$$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.
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Related Book For
Matrices With Applications In Statistics
ISBN: 9780534980382
2nd Edition
Authors: Franklin A Graybill
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