5.6. Let f(x)= exp (u(0,)v(x) + a(x) + b(0)), i = 1, 2, where u and b are functions of 8₁, i = 1, 2, and v and a are functions of x, with ff(x) dx = 1. Show that J(1, 2) = (u(0₂) - u(0₂))(E₁(v(x)) - E₂(v(x))), where E(v(x)) is the expected value of v(x) in the distribution with f(x), i = 1, 2. [See Huzurbazar (1955) for the multivariate, multiparameter, distributions admitting sufficient statistics.]

MATLAB: An Introduction with Applications
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5.6. Let f(x) = exp (u(0,)v(x) + a(x) + b(0₂)), i = 1, 2, where u and b are
functions of 0₁, i = 1, 2, and v and a are functions of x, with ff(x) dx = 1.
Show that J(1, 2) = (u(0₂) - u(0₂))(E₁₂(v(x)) - E₂(v(x))), where E(v(x)) is the
expected value of v(x) in the distribution with f(x), i = 1, 2. [See Huzurbazar
(1955) for the multivariate, multiparameter, distributions admitting sufficient
statistics.]
Transcribed Image Text:5.6. Let f(x) = exp (u(0,)v(x) + a(x) + b(0₂)), i = 1, 2, where u and b are functions of 0₁, i = 1, 2, and v and a are functions of x, with ff(x) dx = 1. Show that J(1, 2) = (u(0₂) - u(0₂))(E₁₂(v(x)) - E₂(v(x))), where E(v(x)) is the expected value of v(x) in the distribution with f(x), i = 1, 2. [See Huzurbazar (1955) for the multivariate, multiparameter, distributions admitting sufficient statistics.]
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