Let X1...Xn be observations such that E(Xi)=u, Var(Xi)=02, and li – j] = 1 Cov(Xị,X;) =...
5. Let X1,X2, . , Xn be a random sample from a distribution with finite variance. Show that (i) COV(Xi-X, X )-0 f ) ρ (Xi-XX,-X)--n-1, 1 # J, 1,,-1, , n. OV&.for any two random variables X and Y) or each 1, and (11 CoV(X,Y) var(x)var(y) (Recall that p vararo 5. Let X1,X2, . , Xn be a random sample from a distribution with finite variance. Show that (i) COV(Xi-X, X )-0 f ) ρ (Xi-XX,-X)--n-1, 1 # J,...
Problem 4 Suppose X1, ..., Xn ~ f(x) independently. Let u = E(Xi) and o2 = Var(Xi). Let X Xi/n. (1) Calculate E(X) and Var(X) (2) Explain that X -> u as n -> co. What is the shape of the density of X? (3) Let XiBernoulli(p), calculate u and a2 in terms of p. (4) Continue from (3), explain that X is the frequency of heads. Calculate E(X) and Var(X). Explain that X -> p. What is the shape...
Let X1....,Xn be a sample of size n from a distribution with expectation u and variance sigma^2 and let u = (2X1+X2+...+Xn-1+2Xn)/(n+1) be an estimator for u. u is consistent,asymptotically unbiased ,unbiased?
Let X1, ..., X., be i.i.d random variables N(u, 02) where u is known parameter and o2 is the unknown parameter. Let y() = 02. (i) Find the CRLB for yo?). (ii) Recall that S2 is an unbiased estimator for o2. Compare the Var(S2) to that of the CRLB for
1. Let X1, . . . , Xn be a sample of size n from a distribution with expectation μ (2X1 + X2 + . . . + Xn-1 + 2Xn)/(n+1)l be an estimator and variance σ . and let μ- for μ. Is it unbiased? asymptotically unbiased? consistent?
, X,' up N(μ, σ2), with σ2 known. Let μη-Xn + 5. Let Xi, of u be an estimator (a) Is ,hi an unbiased estimator for μ? (b) For a particular fixed n, find the distribution of (c) Find the mean squared error (MSE) of . (d) Prove that μη is consistent for μ
Thank you! 5. Let S2 be calculated from a random sample X1,..., Xn with Var(Xi) = 02. We showed in class that E[S2] = 02. Prove that E[S] <o. (Hint: use the fact that the variance of any random variable is always non-negative.)
Observations X1,..., Xn are independent identically distributed, following the PDF fx:(xi) = 0x8-1, and that 0<Xi <1 for all i. The parameter is an unknown positive number. Find the ML estimator of e
2. Let X1,..., Xn be i.i.d. according to a normal distribution N(u,02). (a) Get a sufficient statistic for u. Show your work. (b) Find the maximum likelihood estimator for u. (c) Show that the MLE in part (b) is an unbiased estimator for u. (d) Using Basu's theorem, prove that your MLE from before and sº, the sample variance, are independent. (Hint: use W; = X1-0 and (n-1)32)
0 and an Let X1, X2, ..., Xn be a random sample where each X; follows a normal distribution with mean u unknown standard deviation o. Let K (n-1)s2 = n 202 (a) [2 points] Assume K ~ Gamma(a = n71,8 bias for K. *). We wish to use K as an estimator of o2. Compute the n (b) [1 point] If K is a biased estimator for o?, state the function of K that would make it an unbiased...