Please answer question (a) X1 - X X2 – Å a. Let X1, ..., Xn i.i.d....
Answer the following questions: a. Let X1, X2, . . . , Xn be i.i.d. random vectors (a random sample) from Np(μ1, Σ). Find the distribution of X ̄ . Note: X ̄ = 1/n Xi . b. Refer to question (a). Consider the following two random variables: Q1 = 1′X ̄/1'1 and Q2 = 1′Σ−1X ̄/1′Σ−11 ̄ . Find the mean and variance of Q1 and Q2 .
Q3 Suppose X1, X2, ..., Xn are i.i.d. Poisson random variables with expected value ). It is well-known that X is an unbiased estimator for l because I = E(X). 1. Show that X1+Xn is also an unbiased estimator for \. 2 2. Show that S2 (Xi-X) = is also an unbaised esimator for \. n-1 3. Find MSE(S2). (We will need two facts) E com/questions/2476527/variance-of-sample-variance) 2. Fact 2: For Poisson distribution, E[(X – u)4] 312 + 1. (See for...
Find the variance assuming X1, X2, · · · , Xn be an i.i.d. sample from the density f (x|θ) = 1/2θ e (−|x|/θ) , −∞ < x < ∞
Please show step by step solution. 7. Let X1, X2, ..., Xn be i.i.d. random variables drawn from a N(u,0%). Show that the Sample Variance (52) and the Maximum Likelihood Estimator (S) of o2 are both Consistent Estimators for o?. S2 27=2(X-X)2 and S 21-2(X;-) n-1 n (n-1)S Hint: has a Chi-Square Distr. with (n − 1) degrees of freedom. E(x{n-1)) = n-1,V(xin-1)) = 2(n − 1)
Square of a standard normal: let X1, ..., Xn ~ X be i.i.d. standard normal variables. What is the mean E[X2] and variance Var [X2] of the random variable x?? E[X2] = Var [X2]
9 Let Xi, X2, ..., Xn be an independent trials process with normal density of mean 1 and variance 2. Find the moment generating function for (a) X (b) S2 =X1 + X2 . (c) Sn=X1+X2 + . . . + Xn. (d) An -Sn/n 9 Let Xi, X2, ..., Xn be an independent trials process with normal density of mean 1 and variance 2. Find the moment generating function for (a) X (b) S2 =X1 + X2 . (c)...
7. Let X1 , Xn be i.i.d. with the density p(r,0) = a*(1 - 0)1-k1{x = 0,1} (a) Find the ML estimator of 0 (b) Is it unbiased? (c) Compute its MSE 7. Let X1 , Xn be i.i.d. with the density p(r,0) = a*(1 - 0)1-k1{x = 0,1} (a) Find the ML estimator of 0 (b) Is it unbiased? (c) Compute its MSE
Suppose X1, X2, . . . , Xn are i.i.d. Exp(µ) with the density f(x) = for x>0 (a) Use method of moments to find estimators for µ and µ^2 . (b) What is the log likelihood as a function of µ after observing X1 = x1, . . . , Xn = xn? (c) Find the MLEs for µ and µ^2 . Are they the same as those you find in part (a)? (d) According to the Central Limit...
Answer the following questions: a. Let X1, X2. . . . . Xn be i..d. random vectors (a random sample) from Mpță Σ). Find the distribution of X. Note: X-ri Xi. b. Refer to question (a). Consider the following two random variables: Q1 and 1'1 Q2-1'Σǐ8. Find the mean and variance of (i and (2 1
Additional Question Fix θ > 0 and let X1, . . . , Xn i.i.d. ∼ Unif[0, θ]. We saw in class that the MLE of θ, ˆθMLE = max(X1, . . . , Xn), is biased. I give two other estimators of θ, which can be made unbiased by appropriate choice of constants C1, C2: ˆθ1 = C1 max(X1, . . . , Xn) and ˆθ2 = C2Σxi We have two questions: (1) Find values of C1, C2 for...