Let X1,…, Xn be a sample of iid random variable with pdf f (x; ?) = 1/(2x−?+1) on S = {?, ? + 1, ? + 2,…} with Θ = ℕ.
Determine
a) a sufficient statistic for ?.
b) F(1)(x).
c) f(1)(x).
d) E[X(1)].
Let X1,…, Xn be a sample of iid random variable with pdf f (x; ?) =...
Let X ∼ Geo(?) with Θ=[0, 1]. a) Show that pdf of the random variable X is in the one-parameter regular exponential family of distributions. b) If X1,…, Xn is a sample of iid Geo(?) random variables with Θ=(0, 1), determine a complete minimal sufficient statistic for ?.
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
Let X1, ..., Xn be a random sample from a population with pdf f(x 1/8,0 < x < θ, zero elsewhere. Let Yi < < Y, be the order statistics. Show that Y/Yn and Yn are independent random variables
Let X1 Xn be a random sample from a distribution with the pdf f(x(9) = θ(1 +0)-r(0-1) (1-2), 0 < x < 1, θ > 0. the estimator T-4 is a method of moments estimator for θ. It can be shown that the asymptotic distribution of T is Normal with ETT θ and Var(T) 0042)2 Apply the integral transform method (provide an equation that should be solved to obtain random observations from the distribution) to generate a sam ple of...
Let X1, ..., Xn be a random sample from a distribution with pdf 2πσχ (a) If σ and μ are both unknown, find a minimal sufficient statistic T. (b) If σ is known and μ is unknown, is T from last part a sufficient statistic? Is it a minimal sufficient statistic? Prove your answer. (c) Let V (II1 X)/m, what is the distribution of V? Are V andindependently distributed? Let X1, ..., Xn be a random sample from a distribution...
Q2: ALL STUDENTS (10 Marks] Let X1, ..., Xn be a random sample from the pdf f(x|0) = 0x-?, O<O<O<0. (a) (3 marks) What is a sufficient statistic for 0? (b) (4 marks) Find the MLE of 0. (c) (3 marks) Find the method of moments estimator of 0.
Again, let X1,..., Xn be iid observations from the Uniform(0,0) distribution. (a) Find the joint pdf of Xi) and X(n)- (b) Define R = X(n)-X(1) as the sample range. Find the pdf of R. (c) It turns out, if Xi, . . . , xn (iid) Uniform(0,0), E(R)-θ . What happens to E® as n increases? Briefly explain in words why this makes sense intuitively.
6.4.3. Let X1, X2, ..., Xn be iid, each with the distribution having pdf f(x; 01, 02) = (1/02)e-(2–01)/02, 01 < x <ao, -20 < 02 < 0o, zero elsewhere. Find the maximum likelihood estimators of 01 and 02.
Let X1, X2, ... , Xn be a random sample of size n from the exponential distribution whose pdf is f(x; θ) = (1/θ)e^(−x/θ) , 0 < x < ∞, 0 <θ< ∞. Find the MVUE for θ. Let X1, X2, ... , Xn be a random sample of size n from the exponential distribution whose pdf is f(x; θ) = θe^(−θx) , 0 < x < ∞, 0 <θ< ∞. Find the MVUE for θ.
Let (X1, ... , Xn) be an iid sample from the exponentially distributed X with pdf given by f(x;0) = -e ô, x > 0, 0 >0. Use the Neyman-Pearson Lemma to find the a-level most powerful test (MPT) of Ho : 0 = 2 vs H : 0 = 3.