Question

In: Statistics and Probability

Suppose that X1,. . . , Xn is an m.a. of a distribution U (0, θ]....

Suppose that X1,. . . , Xn is an m.a. of a distribution U (0, θ].
(a) Find the most powerful test of size α to test H0: θ = θ0 vs Ha:
θ = θa, where θa <θ0.
(b) Is the test obtained in part (a) the UMP (α) to test H0: θ = θ0 vs Ha:
θ <θ0 ?.
(c) Find the most powerful test of size α to test H0: θ = θ0 vs Ha: θ =
θa, where θa> θ0.
(d) Is the test obtained in part (c) the UMP (α) to test H0: θ = θ0 vs Ha:
θ> θ0 ?.
(e) Are the most powerful tests of size α found in (a) and (c) unique?

Solutions

Expert Solution


Related Solutions

Suppose that (X1, · · · , Xn) is a sample from the normal distribution N(θ,...
Suppose that (X1, · · · , Xn) is a sample from the normal distribution N(θ, θ^2 ) with θ ∈ R. Find an MLE of θ.
Suppose X1, ..., Xn are i.i.d. from an exponential distribution with mean θ. If we are...
Suppose X1, ..., Xn are i.i.d. from an exponential distribution with mean θ. If we are testing H0 : θ = θ0 vs Ha : θ > θ0. Suppose we reject H0 when ( X¯n/ θ0) > 1 + (1.645/ √n) (a) (10 points) Calculate the power function G(ζ). You may leave your answer in terms of the standard normal cdf Φ(x). (b) (5 points) Is this test consistent?
X1, . . . , Xn are random sample from Uniforma(0, θ), θ > 0. Construct...
X1, . . . , Xn are random sample from Uniforma(0, θ), θ > 0. Construct a consistent estimator for θ based on X(n) .
Suppose X1; : : : ; Xn is i.i.d Exponential distribution with density f(xjθ) = (1/θ)...
Suppose X1; : : : ; Xn is i.i.d Exponential distribution with density f(xjθ) = (1/θ) * e(-x/θ); 0 ≤ x < 1; θ > 0: (a) Find the UMVUE (the best unbiased estimator) of θ. (b) What is the Cramer-Rao lower bound of all unbiased estimator of all unbiased estimator of θ. Does the estimator from (a) attain the lower bound? Justify your answer. (c) What is the Cramer-Rao lower bound of all unbiased estimator of θ^2? 3 (d)...
Let X1, . . . , Xn ∼ iid Unif(0, θ). (a) Is this family MLR...
Let X1, . . . , Xn ∼ iid Unif(0, θ). (a) Is this family MLR in Y = X(n)? (b) Find the UMP size-α test for H0 : θ ≤ θ0 vs H1 : θ > θ0. (c) Find the UMP size-α test for H0 : θ ≥ θ0 vs H1 : θ < θ0. (d) Letting R1 be the rejection region for the test in part (b) and R2 be the rejection region for the test in part...
Let X1, . . . , Xn be i.i.d. samples from Uniform(0, θ). Show that for...
Let X1, . . . , Xn be i.i.d. samples from Uniform(0, θ). Show that for any α ∈ (0, 1), there is a cn,α, such that [max(X1,...,Xn),cn,α max(X1,...,Xn)] is a 1−α confidence interval of θ.
Let X1,…, Xn be a sample of iid N(0, ?) random variables with Θ=(0, ∞). Determine...
Let X1,…, Xn be a sample of iid N(0, ?) random variables with Θ=(0, ∞). Determine a) the MLE ? of ?. b) E(? ̂). c) the asymptotic variance of the MLE of ?. d) the MLE of SD(Xi ) = √ ?.
For a fixed θ>0, let X1,X2,…,Xn be i.i.d., each with the beta (1,θ) density. i) Find...
For a fixed θ>0, let X1,X2,…,Xn be i.i.d., each with the beta (1,θ) density. i) Find θ^ that is the maximum likelihood estimate of θ. ii) Let X have the beta (1,θ) density. Find the density of −log⁡(1−X). Recognize this as one of the famous ones and provide its name and parameters. iii) Find f that is the density of the MLE θ^ in part (i).
Let X1, . . . , Xn i.i.d. Uniform(θ, θ + 1). Show that: ˆθ1 =...
Let X1, . . . , Xn i.i.d. Uniform(θ, θ + 1). Show that: ˆθ1 = X¯ − 1 2 and ˆθ2 = X(n) − n n + 1 are both consistent estimators for θ.
Let X1. . . . Xn be i.i.d f(x; θ) = θ(1 − θ)^x x =...
Let X1. . . . Xn be i.i.d f(x; θ) = θ(1 − θ)^x x = 0.. Is there a function of θ for which there exists an unbiased estimator of θ whose variance achieves the CRLB? If so, find it
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT