Let Xi....,Xn,..., ~iid Exp(1) and let Yn) be the sample maximum of the first n observations....
Dr. Beldi Qiang STATWOB Flotllework #1 1. Let X.,No X~ be a i.İ.d sample form Exp(1), and Y-Σ-x. (a) Use CLT to get a large sample distribution of Y (b) For n 100, give an approximation for P(Y> 100) (c) Let X be the sample mean, then approximate P(.IX <1.2) for n 100. x, from CDF F(r)-1-1/z for 1 e li,00) and ,ero 2Consider a random sample Xi.x, 、 otherwise. (a) Find the limiting distribution of Xim the smallest order...
Let Xi, X2...-Xn be a iid. sample from Bernoulli(p) and let Yn-Σηι(X-P)/n. Show that Ya converges to a degenerate distribution at 0 as n-o.
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.
3. Let Xi, . . . , Xn be iid randoln variables with mean μ and variance σ2. Let, X denote the sample mean and V-Σ, (X,-X)2. (a) Derive the expected values of X and V. (b) Further suppose that Xi,-.,X, are normally distributed. Let Anxn ((a)) an orthogonal matrix whose first rOw 1S be , ..*) and iet Y = AX, where Y (Yİ, ,%), ard X-(XI, , X.), are (column) vectors. (It is not necessary to know aij...
& Let Yn = ao Xn ta, x n- do xn + a, Xn-1 ; n =1,2,... where Xi are iid RVs u ; n = 1, 2, with equal moon o and va siance 2.1 95 { yn in 21% SSS? Is {Yn: n 21 } WSS?
1. Suppose X1, ..., Xn be a random sample from Exp(1) and Y1 < ... < Yn be the order statistics from this sample. a) Find the joint pdf of (Y1, .. , Yn). b) Find the joint pdf of (W1, .. , Wn) where W1 = nY1, W2 = (n-1)(Y2 -Y1), W3 = (n - 2)(Y3 - Y2),..., Wn-1 = 2(Yn-1 - Yn-2), Wn = Yn - Yn-1. (c) Show that Wi's are independent and its distribution is identically...
1. Let Xi,X2,.... Xn be an id sample from a Uniform(0,6) distribution. Let X(n) be the maximum order statistic, and let UX()/e. a) Find the CDF of U b) Is U a pivotal quantity? why or why not? c) Use U to construct a 95% CI for
2. Consider a random sample XI, X2 otherwise. Xn fronn CDF F(x) = 1-1/z for z e [ X) = 1-1/1 for x 1, oo) and zero (a) Find the limiting distribution of X1:n, the smallest order statistic. (b) Find the limiting distribution of X1: (c) Find the limiting distribution of n In X1m
I don't understand a iii and b ii, What's the procedure of deriving the limit distribution? Thanks. 6. Extreme values are of central importance in risk management and the following two questions provide the fundamental tool used in the extreme value theory. (a) Let Xi,... , Xn be independent identically distributed (i. i. d.) exp (1) random variables and define max(Xi,..., Xn) (i) Find the cumulative distribution of Zn (ii) Calculate the cumulative distribution of Vn -Zn - Inn (iii)...
1. Let X1,... , Xn be IID random points from Exp(1/B). The PDF of Exp(1/B) is for x 〉 0. Let X,-1 Σー X, be the sample average. Let 3 be the parameter of interest that we want to estimate. Xi be the sample average. Let B be the parameter of (a) (1 pt) What is the bias and variance of using the sample average Xn as the estimator of 3? (b) (0.5 pt) What is the mean square error...