The joint probability mass function of X is
Now, according to Fisher's Factorization theorem, we can write
where
and
So,
will be sufficient statistic for
2. Let X be a continuous r.v. with pdf f () and cdf F(x). Let U F (X). Show that, as long as F(x) is strictly monotonic increasing, U is uniformly distributed on (0,1). Discuss why this result is important, given that it is known how to simulate Uniformly distributed random variables easily.
3.18 Let the r.v. X has the Geometric p.d.f. (i) Show that X is both sufficient and complete. U(X )-1 (ii) Show that the estimate U defined by: estimate of 6 if X-1, and U(X) -0 if X 2 2, is an unbiased (iii) Conclude that U is the UNU estimate of θ and also an entirely unreasonable estimate.
1.(c)
2.(a),(b)
5. Let Xi,..., X, be iid N(e, 1). (a) Show that X is a complete sufficient statistic. (b) Show that the UMVUE of θ 2 is X2-1/n x"-'e-x/θ , x > 0.0 > 0 6. Let Xi, ,Xn be i.i.d. gamma(α,6) where α > l is known. ( f(x) Γ(α)θα (a) Show that Σ X, is complete and sufficient for θ (b) Find ElI/X] (c) Find the UMVUE of 1/0 -e λ , X > 0 2) (x...
Let f(x; θ) = 1 θ x 1−θ θ for 0 < x < 1, 0 < θ < ∞.
(1) Show that ˆθ = − 1 n Pn i=1 log(Xi) is the MLE of θ. (2) Show
that this MLE is unbiased.
Exactly 6.4-8. Let f(x:0)-缸붕 for 0 < x < 1,0 < θ < oo 1 1-0 (1) Show that θ Σ-1 log(X) is the MLE of θ (2) Show that this MLE is unbiased.
Let X1,X2,,X be a random sample from a distribution function f(x,8) = θ"(1-8)1-r for x = 0,1 (a) Show that Y = Σ.1X, is a sufficient statistic for θ. (i) Find a function of Y that is an unbiased estimate for θ (ii) Hence, explain why this function is the minimum variance unbiased estimator(MVUE) for θ (c) Is1-the MVUE for Please explain.
Practice Exam Questions 2 Let X be a r.v. with density function x 2 1 a. Determine the distribution function of X, i.e. F(x). Find E(X) and V(X) b. Find the MLE estimator of θ constructed from a sample Xi,Xn c. Is the estimator find in (b) biased?
Practice Exam Questions 2 Let X be a r.v. with density function x 2 1 a. Determine the distribution function of X, i.e. F(x). Find E(X) and V(X) b. Find the MLE...
5.7 Let X, X, be independent r.v.'s from the u(e -a, o+ b) distribution, where a and b are (known) positive constants and θ Ω M. Determine the moment estimate θ of θ, and compute its expectation and variance.
Exercise 3.16: A sample of n independent observations is taken on a rv. X having a logarithmic series distribution, x=1, 2, EWT-0), , x In . Show that the MLE θ of θ where θ is an unknown parameter in the range (0,1) satisfies the equation e+ ž(1-0) ln(1-9-0, Fuercio ti tample mean. Find the asymptotie distribution oftå.
Exercise 3.16: A sample of n independent observations is taken on a rv. X having a logarithmic series distribution, x=1, 2, EWT-0),...
2.6 the function f(x θ)-6x-(θ+1), x 2 lde Ω-(0,0) is a p.d.f. (ii) On the basis of a random sample of size n from this pdf., show that the statistic X, sufficient for θ X is
Let A be n × n with AT-A. (The matrix A is syrnmetric.) Let B be 1 × n and let c E R. Define f : Rn → R by f(x) = 2.7, A . x + B . x + c. Show that The function f is a quadratic function
Let A be n × n with AT-A. (The matrix A is syrnmetric.) Let B be 1 × n and let c E R. Define f : Rn...