



Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
The instructions and questions for a final exam in a statistical inference course. The exam covers topics such as decision rules, james-stein theory, bayesian inference, and markov chain monte carlo (mcmc). Students are required to answer each question specifically and circle the correct answer for multiple choice questions.
Typology: Exams
1 / 5
This page cannot be seen from the preview
Don't miss anything!




December 13, 2005 Final Exam
Instructions: Answer each question on the test paper provided. Circle the correct answer on multiple choice questions. Be specific on short-answer questions. Each multiple choice question is worth four points, and each of the other questions is worth 12 points. Have a happy holiday!
π(μ, σ) = σ^1 φ
( (^) μ σ
) · 2 φ(σ)I(0,∞)(σ),
where φ is the standard normal density and I(0,∞) is an indicator function. In this particular problem, the prior π is (a) a noninformative prior. (b) a conjugate prior. (c) an improper prior. (d) none of the above. (e) saddened at the passing of his buddy Richard Pryor.
π(θ) ∝ θa−^1 (1 − θ)b−^1 I(0,1)(θ),
if a > 1 and b > 1 then the posterior mean is (a) equal to the posterior mode. (b) equal to the usual frequentist estimate of θ. (c) a weighted average of the means of two beta distributions. (d) all of the above. (e) often confused with the more popular Bayes point estimate known as the “rump me- dian.”
( θ − (^12)
) 2 , 0 ≤ θ ≤ 1 R(θ, δ 3 ) = 7
∣∣ ∣∣θ − 1 2
∣∣ ∣∣^3 , 0 ≤ θ ≤ 1.
If a uniform prior is used to compute the Bayes risk for each rule, then the respective minimax and Bayes rules are (a) δ 3 and δ 2. (b) δ 1 and δ 3. (c) δ 2 and δ 3. (d) δ 2 and δ 1. (e) impossible to determine given the amount of sleep I had last night.
P (M 1 ) =^12 , P (M 2 ) =^14 , and P (M 3 ) =^14.
Write down an expression for P (M 1 |y) in terms of the quantities defined above.