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3. Fix w = [W0, W1,..., WM] ER M+1 and 0. Let 1,..., N be independent Gaussian RVs where (x;; w,) ~ N($(x) Tw,)
3. Fix w = [W0, W1,..., WM] ER M+1 and 0. Let 1,..., N be independent Gaussian RVs where (x;; w,) ~ N($(x) Tw,) for i = {1,..., N}, where (x) = [1,x,...,x]T. Show that the joint likelihood function for observing the values y,..., YN is given by where 1 L(y1,..., YN; W,) = (2) -N/2 exp ||Y-Xw| 202 (5) 1 X1 xM Y = [y1,..., YN] R, X= : X2 RNXM (6) ...
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An Introduction to the Mathematics of Financial Derivatives
Authors: Ali Hirsa, Salih N. Neftci
3rd edition
012384682X, 978-0123846822
