1. Let X1, X2,... be independent random variables each with the standard normal distribution, and for...
1. Let Xi, X2,... be independent random variables each with the standard normal distribution, and for each n 2 0 let Sn-1 Xi. Use importance sampling to obtain good estimates for each of the following probabilities: (a) Pfmaxn<100 Sn> 10; and (b) Pímaxns100 Sn > 30) HINTS: The basic identity of importance sampling implies that d.P n100 where Po is the probability measure under which the random variables Xi, X2,... are independent normals with mean 0 amd variance 1. The...
Let X1 and X2 be two independent standard normal random variables. Define two new random variables as follows: Y-Xi X2 and Y2- XiBX2. You are not given the constant B but it is known that Cov(Yi, Y2)-0. Find (a) the density of Y (b) Cov(X2, Y2)
Let Xi and X2 independent random variables, with distribution functions F1, and F2, respectively Let Y a Bernoulli random variable with parameter p. Suppose that Y, X1 and X2 are independent. Proof using the de finition of distribution function that the the distribution function of Z =Y Xit(1-Y)X2 is F = pF14(1-p)F2 Don't use generatinq moment functions, characteristic functions) Xi and X2 independent random variables, with distribution functions F1, and F2, respectively Let Y a Bernoulli random variable with parameter...
4 points) Let X1, X2 be independent random variables, with X1 uniform on (3,9) and X2 uniform on (3, 12). Find the joint density of Y = X/X2 and Z = Xi X2 on the support of Y, Z. f(y, z) =
5. (4 points) Let X1, X2, be independent random variables that are uniformly distributed on [-1,1] Show that the sequence Yi,Y2, converges in probability to some limit, and identity the limit, for each of the following cases: (a) Yn = max Xi, , xn (this is similar to an example from class). (c) Yn = (Xn)"
3. Suppose X1, X2, -- are independent identically distributed random variables with mean 0 and variance 1.Let Sn denote the partial sum Let Fn denote the information contained in Xi, .X,. Suppoe m n. (1) Compute El(Sn Sm)lFm (2) Compute ESm(Sn Sm)|F (3) Compute ES|]. (Hint: Write S (4) Verify that S -n is a martingale. [Sm(Sn Sm))2) 3. Suppose X1, X2, -- are independent identically distributed random variables with mean 0 and variance 1.Let Sn denote the partial sum...
a) If X1 and X2 are independent random variables and X1 tollows the Nor nalLA σ1 X, +X2 follow? di tri t on and X to ows the Nonna μα 2 distribution, ne ha distribution do b) IfX1 , X2 . X, , arendependent random variables and each Xk follows the NormalA 에 ds rbutio. then what distribution does follow? , n L.6) Generating functions for sums of independent random variables a) If X and X are independent random variables,...
Let x1, x2, x3, x4 be independent standard normal random variables. Show that , , are independent and each follows a distribution (x1 - r2)
14. Let X1, X2, X3 be independent random variables that represent lifetimes (in hours) of three key components of a device. Suppose their respective distributions are exponential with means 1000, 1500, and 2000. Let Y be the minimum of Xi, X2, X3 and compute P(Y 1000).
Exercise 6.48. Let X1, X2, ..., Xin be independent exponential random variables, with parameter lį for Xi. Let Y be the minimum of these random variables. Show that Y ~ Exp(11 +...+ In).