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?
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 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 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
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 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 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