Page 525 - Probability and Statistical Inference
        P. 525
     502    10. Bayesian Methods
                                 true average gas mileage per gallon,  . Give the Bayes estimate of the true
                                 average gas mileage per gallon   under the squared error loss.
                                    10.4.10 (Fubinis Theorem) Suppose that a function of two real variables
                                 g(x , x ) is either non-negative or integrable on the space χ = χ  × χ (⊆ ℜ ×
                                    1
                                      2
                                                                                           2
                                                                                       1
                                 ℜ). That is, for all (x , x ) ∈ χ, the function g(x , x ) is either non-negative or
                                                     2
                                                   1
                                                                         1
                                                                           2
                                 integrable. Then, show that the order of the (two-dimensional) integrals can
                                 be interchanged, that is, one can write
                                 {Note: This is a hard result to verify. It is stated here for reference purposes
                                 and completeness. Fubinis Theorem was used in the proof of the Theorem
                                 10.4.1 for changing the order of two integrals.}
                                    10.5.1 (Exercise 10.4.2 Continued) Let X , X  be independent, X  be dis-
                                                                                           1
                                                                       1
                                                                          2
                                 tributed as N (θ, 1) and X  be distributed as N (2θ, 3) given that   = θ where
                                                      2
                                  (∈ ℜ) is the unknown parameter. Let us suppose that the prior distribution
                                 of   on the space Θ = ℜ is N (5, τ ) where τ(> 0) is a known number. With
                                                               2
                                 fixed 0 < α < 1, derive the 100(1  α)% HPD credible interval for  . {Hint:
                                 Use the form of the posterior from the Exercise 10.3.1.}
                                    10.5.2 (Exercise 10.4.3 Continued) Let X , ..., X  be iid Exponential(θ)
                                                                        1
                                                                              n
                                 given that   = θ where the parameter  (> 0) is unknown. Suppose that   has
                                 the IGamma(1, 1) prior pdf h(θ) = θ  exp {1/θ}I(θ > 0). With fixed 0 < α <
                                                               2
                                 1, derive the 100(1  α)% HPD credible interval for  . {Hint: Use the form of
                                 the posterior from the Exercise 10.3.2.}
                                    10.5.3 (Exercise 10.4.4 Continued) Let X , ..., X  be iid N (0, θ ) given that
                                                                                        2
                                                                      1
                                                                            n
                                   = θ where the parameter v(> 0) is unknown. Suppose that   has the
                                 IGamma(1, 1). With fixed 0 < α < 1, derive the 100(1  α)% HPD credible
                                 interval for  . {Hint: Use the form of the posterior from the Exercise 10.3.3.}
                                            2
                                    10.5.4 (Exercise 10.4.5 Continued) Let X , ..., X  be iid Uniform(0, θ)
                                                                              n
                                                                        1
                                 given that   = θ where the parameter  (> 0) is unknown. Suppose that v has
                                 the Pareto(τ, β) prior, that is the prior pdf is given by h(θ) = βτ θ   I(τ < θ
                                                                                      β (β+1)
                                 < ∞) where τ, β are known positive numbers. With fixed 0 < α < 1, derive the
                                 100(1 - a)% HPD credible interval for  . {Hint: Use the form of the posterior
                                 from the Exercise 10.3.4.}
                                    10.5.5 (Exercise 10.4.6 Continued) Let X , ..., X  be iid Uniform(0, aθ)
                                                                        1
                                                                              n
                                 given that   = θ where the parameter  (> 0) is unknown, but a(> 0) is
                                 assumed known. Suppose that   has the Pareto(τ, β) prior where τ, β are





