B1 The x distribution is a special case of Gamma distribution (not to be confused with gamma function; see below). The density function of the Gamma distribution with parameters and k is given by where -1 e -x/0 (x) = = г(k) Øk if x > 0, and otherwise, г(k) = √ ₁ k-1-x dx x' e is the gamma function. (a) For every k ≥ 1, 0 > 0, find the mode of the density. Hint: The algebra can be simplified by appropriate use of logarithms. ~ Now suppose that X1,..., Xn id Exp(\) and that we have a prior belief in A which is consistent with a prior distribution X. Gamma(a, b), for some a, ß, i.e. the prior density of is Baxa-1-BA T(a) e = so 01/ẞ and k = a. (b) Write down the likelihood, and show that the posterior distribution for \ is also a Gamma distribution, but with parameters a +n and B + Σ Xi. (c) Find the mode of the posterior distribution and examine the behaviour as n → ∞.
B1 The x distribution is a special case of Gamma distribution (not to be confused with gamma function; see below). The density function of the Gamma distribution with parameters and k is given by where -1 e -x/0 (x) = = г(k) Øk if x > 0, and otherwise, г(k) = √ ₁ k-1-x dx x' e is the gamma function. (a) For every k ≥ 1, 0 > 0, find the mode of the density. Hint: The algebra can be simplified by appropriate use of logarithms. ~ Now suppose that X1,..., Xn id Exp(\) and that we have a prior belief in A which is consistent with a prior distribution X. Gamma(a, b), for some a, ß, i.e. the prior density of is Baxa-1-BA T(a) e = so 01/ẞ and k = a. (b) Write down the likelihood, and show that the posterior distribution for \ is also a Gamma distribution, but with parameters a +n and B + Σ Xi. (c) Find the mode of the posterior distribution and examine the behaviour as n → ∞.
A First Course in Probability (10th Edition)
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ISBN:9780134753119
Author:Sheldon Ross
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Chapter1: Combinatorial Analysis
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Transcribed Image Text:B1 The x distribution is a special case of Gamma distribution (not to be confused with gamma
function; see below). The density function of the Gamma distribution with parameters
and k is given by
where
-1
e
-x/0
(x) =
=
г(k) Øk
if x > 0, and
otherwise,
г(k) = √ ₁
k-1-x dx
x' e
is the gamma function.
(a) For every k ≥ 1, 0 > 0, find the mode of the density. Hint: The algebra can be
simplified by appropriate use of logarithms.
~
Now suppose that X1,..., Xn id Exp(\) and that we have a prior belief in A which is
consistent with a prior distribution X. Gamma(a, b), for some a, ß, i.e. the prior density
of is
Baxa-1-BA
T(a)
e
=
so 01/ẞ and k = a.
(b) Write down the likelihood, and show that the posterior distribution for \ is also a
Gamma distribution, but with parameters a +n and B + Σ Xi.
(c) Find the mode of the posterior distribution and examine the behaviour as n → ∞.
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