, xn be a sample with joint pdf (or pmf) f(Xn10), θ 3. Let Xi, Θ C R. Suppose that {f(x,10) : θ E Θ} has monotone likelihood ratio (MLR) in T(Xn). Consider test function if T(%) > c Xn if T(%) <...
3. Let X1,..Xn be a sample with joint pdf (or pmf) f(x,0), 0 e 0 c R. Suppose that {f(x, 0) 0 e 0} has monotone likelihood ratio (MLR) in T(X,). Consider test function if T(xn)> c if T(xn) c if T(x)<c 0 E [0,1 and c 2 0 are constants. Prove that the power function of ¢(X,) is where non-decreasing in 0
3. Let X1,..Xn be a sample with joint pdf (or pmf) f(x,0), 0 e 0 c R....
Power function
sample with joint pdf (or pmf) f (x |0), 0 e 0 c R. Suppose Let X1,..., X,n be a that {f(xn0) : 0 E 0} has monotone likelihood ratio (MLR) in T(X). Consider test function if T(xn)> c 1 if T(Xn) (Xn) C if T(xn)c 0 where y E [0, 1] and c > 0 are constants. Prove that the power function of ø(X,,) is non-decreasing in 0
sample with joint pdf (or pmf) f (x |0),...
2. (20pts) Let Xi,..., X be a random sample from a population with pdf f(x)--(1 , where θ > 0 and x > 1. (a) Carry out the likelihood ratio tests of Ho : θ-a, versus Hi : θ a-show that the likelihod ratio statistic corresponding to this test, A, can be re-written as Λ = cYne-ouY, where Y Σ:.. In (X), and the constant c depends on n and θο but not on Y. (b) Make a sketch of...
Let Xi,... , Xn be a random sample from a normal random variable X with E(X) 0 and var(X)-0, i.e., X ~N(0,0) (a) What is the pdf of X? (b) Find the likelihood function, L(0), and the log-likelihood function, e(0) (c) Find the maximun likelihood estimator of θ, θ (d) Is θ unbiased?
5. Let Xi, . . . , Xn be a random sample from f(x:0) = -| for z > 0. (a) Assume that θ 0.2 Using the Inversion Method of Sampling, write a R function to generate data from f(x; 0). (b) Use your function in (a) to draw a sample of size 100 from f(0 0.2 (c) Find the method of moments estimate of θ using the data in (b). (d) Find the maximum likelihood estimate of θ using...
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...
Suppose that Xi, X2, ..., Xn is an iid sample from the distribution with density where θ > 0. (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
Let Xi, X2, Xn be ar ensity function f(r; θ) = (1/2)e-Iz-이,-oo < x < 00,-00 < θ < oo. Find the d MLE θ
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...
Let X1,..., Xn be a random sample from the pdf f(x:0)-82-2, 0 < θ x < oo. (a) Find the method of moments estimator of θ. (b) Find the maxinum likelihood estimator of θ