Probability and Measure;
Recall the definition:
Probability and Measure; Recall the definition: Show the following Xn → X and Yn y then...
1. A sequence of random variables Xn satisfy Xn _>X in probability and E(Xn) -> E(X) for some random variable X (a) Show that E([X, - X|) -> 0 if Xn >0 for all n (b) Find a counterexample satisfying E(X,n - X) A0 if X are not non-negative. 1. A sequence of random variables Xn satisfy Xn _>X in probability and E(Xn) -> E(X) for some random variable X (a) Show that E([X, - X|) -> 0 if Xn...
number 3 please Hw4.1708.pd 1 2 TL (2) LP convergence vs. convergence in probability Let Xn, nNbe a sequence of random variables and let X be another random variable. Given l < p < oo, we say that Xn converges to X in Lp if E(Xn-X") → 0 as n → x Show that this implies that Xn converges to X in probability (3) Monte Carlo Let f : 10, 1] → R be continuous and let Xn, n on...
2. Let Xn ~ NG, Intuitivel y, Xn will concentrate at as n -o. In this question, we will justify this intuition using the convergence concepts we learned (a) Show that Xn, 4> 1/2. (Recall for a random variable X which takes value 1/2 with all probability, its c.d.f. Fo is given by Fo(t) 0 for all t< 1/2, Fo(t)1 for all t 2 1/2. You need then to show the c.d.f. of Xn, say F(t), converges to Fo(t) at...
#s 2, 3, 6 2. Let (En)acy be a sequence in R (a) Show that xn → oo if and only if-An →-oo. (b) If xn > 0 for all n in N, show that linnAn = 0 if and only if lim-= oo. 3. Let ()nEN be a sequence in R. (a) If x <0 for all n in N, show that - -oo if and only if xl 0o. (b) Show, by example, that if kal → oo,...
Consider two sequences of random variables X1, X2,... and Y1, Y., .... Suppose that Xn converges to a and Y, converges to b with probability 1. Show that X, + Y, converges to a+b, with probability 1. Next, we assume that the random variables Y cannot be equal to zero, show that X/Y, converges to a/b with probability 1.
Write out a sequence of random variables {Xn}, n=1,2,…such that Xn converges to 0 in probability but {E(Xn), n=1,2,…} does not converge to 0. Prove it.
1) Let X and Y be random variables. Show that Cov( X + Y, X-Y) Var(X)--Var(Y) without appealing to the general formulas for the covariance of the linear combinations of sets of random variables; use the basic identity Cov(Z1,22)-E[Z1Z2]- E[Z1 E[Z2, valid for any two random variables, and the properties of the expected value 2) Let X be the normal random variable with zero mean and standard deviation Let ?(t) be the distribution function of the standard normal random variable....
5. Let {xn} and {yn} be sequences of real numbers such that x1 = 2 and y1 = 8 and for n = 1,2,3,··· x2nyn + xnyn2 x2n + yn2 xn+1 = x2 + y2 and yn+1 = x + y . nn nn (a) Prove that xn+1 − yn+1 = −(x3n − yn3 )(xn − yn) for all positive integers n. (xn +yn)(x2n +yn2) (b) Show that 0 < xn ≤ yn for all positive integers n. Hence, prove...
4. Let X1, X2, . .. be independent random variables satisfying E(X) E(Xn) --fi. (a) Show that Y, = Xn - E(Xn) are independent and E(Yn) = 0, E(Y2) (b) Show that for Y, = (Y1 + . . + Y,)/n, <B for some finite B > 0 and VB,E(Y) < 16B. 16B 6B 1 E(Y) E(Y) n4 i1 n4 n3 (c) Show that P(Y, > e) < 0 and conclude Y, ->0 almost surely (d) Show that (i1 +...
3. (a) (5 points) Let Xi,... be a sequence of independent identically distributed random variables e of tnduqendent idente onm the interval (o, 1] and let Compute the (almost surely) limit of Yn (b) (5 points) Let X1, X2,... be independent randon variables such that Xn is a discrete random variable uniform on the set {1, 2, . . . , n + 1]. Let Yn = min(X1,X2, . . . , Xn} be the smallest value among Xj,Xn. Show...