Suppose Yi,...Yn are exponentially distributed: YiExp(A) (b) Find Jeffreys' prior, and express this as a member...
10. Suppose Y1, ..., Yn are a random sample from a population with density fylu(u) = a exp(- (logyH)") for y > 0. Our interest is in estimating u. (a) Determine a conjugate family of prior densities, and find the posterior density. (b) What is the Bayesian posterior mean estimate for u?!
3. Suppose that Xi,.... Xn is a random sample from a uniform distribution over [0,0) That is, 0 elsewhere Also suppose that the prior distribution of θ is a Pareto distribution with density 0 elsewhere where θ0 > 0 and α > 1. (a) Determine (b) Show , θ > max(T1 , . . . ,Zn,%) and hence deduce the posterior density of θ given x, . . . ,Zn is (c) Compute the mean of the posterior distribution and...
2) Let Yi,., Yn be iid N(a,a2). Let a~ known Find the posterior distribution p(u|3y). This distribution will depend N (8, T2) and trcat o2, 6, and r2 as fixed and on 2, 6, and 2. Calculations are tedious here. Use the hints given in class and follow through 2) Let Yi,., Yn be iid N(a,a2). Let a~ known Find the posterior distribution p(u|3y). This distribution will depend N (8, T2) and trcat o2, 6, and r2 as fixed and...
Question 3 Assume 21, 22, ..., In are normally distributed with mean y and variance o2. Hold o2 constant. (a) Show that this distribution is in the exponential family. (b) What is the conjugate prior? Express in canonical form. (c) What is the posterior distribution using the conjugate prior in (b)? Express in canonical form. Challenge question: Repeat (a)-(c) without holding o2 constant.
1. Suppose Yi, ½ . . . , Yn is a random sample of n independent observations from a distribution with pdf 202 fY()otherwise. (a) Find the MLE for θ (c) Use the pivotal quantity to find a 100(1-a)% CI for θ 1. Suppose Yi, ½ . . . , Yn is a random sample of n independent observations from a distribution with pdf 202 fY()otherwise. (a) Find the MLE for θ (c) Use the pivotal quantity to find a...
Suppose that X has the binomial distribution b(p,n). Find the Jeffreys prior for p and the associated Bayes estimator.
4. Suppose Yi, Yn are iid randonn variables with E(X) = μ, Var(y)-σ2 < oo. For large n, find the approximate distribution of p = n Σηι Yi, Be sure to name any theorems you used.
Question 1. Take a moment to convince yourself that the exponential and gamma distributions are exponential family models. Show that, if the data is exponentially distributed as above with a gamma prior q(0) Gamma(00,%) the posterior is again a gamma, and find the formula for the posterior parameters. (In other words, adapt the computation we performed in class for general exponential families to the specific case of the exponential/gamma model.) In detail: Ignore multiplicative constants and normalization terms, such as...
B1. A random sample of n observations, Yi, ., Yn, is selected from a pop- ulation in which Yi, for i = 1, 2, ,n, possesses a common distribution the same as that of the population distribution Y (a) Suppose that we know Y has a Geometric distribution with parameter p, p unknown. Find the estimator using the method of moments. (b) Suppose that we know that Y has an exponential distribution with parameter λ, λ unknown. Find the estimator...