8.33 Let X1, X2, L(X — м), for n 3D 0, 1, 2, .. (a) Show that Zo, Z\, ... is a martingale with respect to be i.d random...
3. Suppose X1,X2, are independent identically distributed random variables with mean μ and variance σ2. Let So = 0 and for n > 0 let Sn denote the partial sumi Let Fn denote the information contained in X1, ,Xn. (1) Verify that Sn nu is a martingale. (2) Assume that μ 0, verify that Sn-nơ2 is a martingale. 3. Suppose X1,X2, are independent identically distributed random variables with mean μ and variance σ2. Let So = 0 and for n...
8. Let X1, X2,...,X, U(0,1) random variables and let M = max(X1, X2,...,xn). - Show that M. 1, that is, M, converges in probability to 1 as n o . - Show that n(1 - M.) Exp(1), that is, n(1 - M.) converges in distribution to an exponential r.v. with mean 1 as n .
Let X1 and X2 be independent random variables so X1~ N(u,1) and X2 N(u,4) Where u R a) Show that the likelihood for , given that X1 = x1 and X2 = xz is 8 4T b) Show, that the maxium likelihood estimate for u is 4x1+ x2 и (х, х2) e) Show that СтN -("x"x) .я d) and enter a formula for the 95% confidence interval for Let X1 and X2 be independent random variables so X1~ N(u,1) and...
6.7. Let X,, be a sequence of independent and identically distributed X, and show Pl random variables with mean 0 and variance σ. Let 1-1 that {Z., n 2 1j is a martingale when 6.7. Let X,, be a sequence of independent and identically distributed X, and show Pl random variables with mean 0 and variance σ. Let 1-1 that {Z., n 2 1j is a martingale when
Let X1, X2, · · · be independent random variables, Xn ∼ U(−1/n, 1/n). Let X be a random variable with P(X = 0) = 1. (a) what is the CDF of Xn? (b) Does Xn converge to X in distribution? in probability?
Let us consider the biased random walk S,-X1 +X2+···+X,, with S: is a sequence of independent randon variables with P(X,--1)-g,P(X.-1) p+q=1 and Mt Show that M.-Sn-b- calculate Elr), where τ = inf{n : S" = a or-6) with a, b > 0. 0. where Xi, X2 p. where g)n is a martingale. Use this martingale to
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...
O. Let X1 and X2 be two random variables, and let Y = (X1 + X2)2. Suppose that E[Y ] = 25 and that the variance of X1 and X2 are 9 and 16, respectively. O. Let Xi and X2 be two random variables, and let Y = (X1 X2)2. Suppose that and that the variance of X1 and X2 are 9 and 16, respectively E[Y] = 25 (63) Suppose that both X\ and X2 have mean zero. Then the...
7. Let X1, X2, ... be an i.i.d. random variables. (a) Show that max(X1,... , X,n)/n >0 in probability if nP(Xn > n) -» 0. (b) Find a random variable Y satisfying nP(Y > n) ->0 and E(Y) = Oo
For a martingale sZ, n 2 1), let X,- Z, - Z,-, i 2 1, where Zo0 Show that Var(Z)-Σ Var(X) 1-1