Suppose that X1, X2, ..., Xn are independent random variables (not iid) with densities ÍXi(z10,) -.2...
Suppose that Xi, X2,..., Xn are independent random variables (not iid) with densities x, (x^, where 6, > 0, for i-1, 2, , n. versus H1: not Ho (c) Suppose Ho is true so that the common distribution of X1, X2,..., Xn, now viewed as being conditional on 6, is described by where θ > 0. Identify a conjugate prior for 0. Specify any hyperparameters in your prior (pick values for fun if you want). Show how to carry out...
Suppose that Xi, X2,..., Xn is an iid sample from r > 0 where θ 0. Consider testing Ho : θ-Bo versus H1: θ (a) Derive a size α likelihood ratio test (LRT). (b) Derive the power function P(0) of the LRT. θο, where θο is known. (c) Now consider putting an inverse gamma prior distribution on θ, namely, 1 00), a 4a where a and b are known. Show how to carry out the Bayesian test (d) Is the...
Suppose X1, X2, .., Xn is an iid sample from where >0. (a) Derive the size α likelihood ratio test (LRT) for Ho : θ-Bo versus H : θ θο. Derive the power function of the LRT (b) Suppose that n 10, Derive the most powerful (MP) level α-0.10 test of Ho : θ 1 versus Hi: 0-2. Calculate the power of your test
4. (30 points) Suppose that we have two independent random samples: X1, X2, ..,,Xn are exponential (9) and Y.Y2, ,,Yn are exponential(A) (aside: be happy l didn't make it(!) a. Find the likelihood ratio test of Ho: θ 1 versus H1 : θ . b. Show that the test in part a. can be based on the statistic ΣΑΜ c. Find the distribution of T when Ho is true.
Conditional on θ, the random variables X1, X2, ,Xn are îid from In turn, the parameter θ is best regarded as random with prior distribution αθ where a 0 is known (a) Find the posterior mean of θ (b) Discuss how you would formulate the Bayesian test of versus Conditional on θ, the random variables X1, X2, ,Xn are îid from In turn, the parameter θ is best regarded as random with prior distribution αθ where a 0 is known...
Suppose that X1, X2,..., Xn are iid from where a 1 is a known constant and θ > 0 is an unknown parameter. (a) Show that the likelihood ratio rejection region for testing Ho : θ θο versus H : θ > θο can be written in terms of X(n), the maximum order statistic. (b) Derive the power function of the test in part (a). (c) Derive the most powerful (MP) level α test of Ho : θ-5 versus H1...
Please justify each step! 4. (30 points) Suppose that we have two independent random samples: X1, X2, ...,, Xn are exponential(8) and Y. Y, , , Yn are exponential(A) (aside: be happy I didn't make it 〈!) a. Find the likelihood ratio test of Ho: θ μ versus H1:0 # . b. Show that the test in part a. can be based on the statistic c. Find the distribution of T when Ho is true. 4. (30 points) Suppose that...
Suppose that X1,X2, ,Xn are iid N(μ, σ2), where both parameters are unknown. Derive the likelihood ratio test (LRT) of Ho : σ2 < σ1 versus Ho : σ2 > σ.. (a) Argue that a LRT will reject Ho when w(x)S2 2 0 is large and find the critical value to confer a size α test. (b) Derive the power function of the LRT
Suppose that Xi, X2, ..., Xn is an iid sample from the distribution with density where θ > 0. (a) Find the maximum likelihood estimator (MLE) of θ (b) Give the form of the likelihood ratio test for Ho : θ-Bo versus H1: θ > θο. (c) Show that there is an appropriate statistic T - T(X) that has monotone likelihood ratio. (d) Derive the uniformly most powerful (UMP) level α test for versusS You must give an explicit expression...
5. We have two independent samples of n observations X1, X2, .. . , Xn and Yı, Y2,.. . , Yn We want to test the hvpothesis H 0 : μΧ-My versus the alternative H1 : μΧ * My (a) First, assume that the null hypothesis Ho is true and find the MLE for μ-Ac-My (b) Then plug this estimate into the log likelihood along with the MLE's μχ-x and My-- to calculate the LRT statistic (c) Is this likelihood...