Suppose that we have data y = (y₁,...,yn). Each data-point is assumed to be generated by a distribution with the following probability density function: p(y; | 4) = 2y; exp(-y?), y₁ ≥ 0, i = 1,..., n. The unknown parameter is, with > 0. A Gamma(a,B) distribution is chosen as the prior distribution for y. Derive the resulting posterior distribution for given y.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.1: Measures Of Center
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Suppose that we have data y = (y₁,..., yn). Each data-point is assumed to be generated by a
distribution with the following probability density function:
p(y; | 4) = 24y; exp(-4y?), y¡ ≥ 0, i = 1,...,n.
The unknown parameter is , with > 0.
A Gamma(a,ß) distribution is chosen as the prior distribution for . Derive the
resulting posterior distribution for given y.
Transcribed Image Text:Suppose that we have data y = (y₁,..., yn). Each data-point is assumed to be generated by a distribution with the following probability density function: p(y; | 4) = 24y; exp(-4y?), y¡ ≥ 0, i = 1,...,n. The unknown parameter is , with > 0. A Gamma(a,ß) distribution is chosen as the prior distribution for . Derive the resulting posterior distribution for given y.
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