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Q4) Assume that a variable x comes from a probability distribution of the form P(x|w) exp(Σwkf(x) 1 Z(w) uſu(x)), where the functions f(x) are given, and the parameters w = {w} are not known. A data set {x(n)} of N points is supplied. Show by differentiating the log likelihood that the maximum-likelihood parameters WML satisfy ΣP(x | WML) fk (x) = ¹ Σ fk. (x(n))

Q4) Assume that a variable x comes from a probability distribution of the form P(x|w) exp(Σwkf(x) 1 Z(w) uſu(x)), where the functions f(x) are given, and the parameters w = {w} are not known. A data set {x(n)} of N points is supplied. Show by differentiating the log likelihood that the maximum-likelihood parameters WML satisfy ΣP(x | WML) fk (x) = ¹ Σ fk. (x(n))

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Q4) Assume that a variable x comes from a probability distribution of the form 1 Su(x)), Z(w) P(x|w): = exp(Σwkf(x) where the functions f(x) are given, and the parameters w = {w} are not known. A data set {x()} of N points is supplied. Show by differentiating the log likelihood that the maximum-likelihood parameters WML satisfy ΣP (x | WML) ƒi (x) = } [ƒk. (x(™)) fk x n
Transcribed Image Text:Q4) Assume that a variable x comes from a probability distribution of the form 1 Su(x)), Z(w) P(x|w): = exp(Σwkf(x) where the functions f(x) are given, and the parameters w = {w} are not known. A data set {x()} of N points is supplied. Show by differentiating the log likelihood that the maximum-likelihood parameters WML satisfy ΣP (x | WML) ƒi (x) = } [ƒk. (x(™)) fk x n
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