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Suppose that the n random variables X1, ..., Xn form a random sample from the discrete distribution with f(k) = ( 2 −(k+1) for k = 0, 1, 2, . . . ; 0 otherwise. Find P(X1 = X2 = ... = Xn).
2. Suppose X1, X2, . .., Xn are a random sample from θ>0 0, otherwise Note: If X~fx(a; 0), thenXEx(0). (a) Find the CRLB of any unbiased estimator of θ (b) Is the MLE for θ the MVUE?
Suppose X1, X2, · · · , Xn form a random sample from a distribution with p.d.f. f(x;?)=(1+?)x?, 0<x<1, ?>0. a. Find the MLE of ?. b. Show that the MLE is sufficient for ?.
Let X1, X2, ..., Xn be a random sample from the distribution with pdf f(3;6) = V porta exp ( 0) 10.02) for some parameter 2 > 0. (a) Find the MLE for 0. (b) Find the Cramér-Rao lower bound for the variance of all unbiased estimators of 0. (c) Find the asymptotic distribution of your MLE from part (a).
Let X1, X2, ..., Xn be a random sample of size n from the distribution with probability density function To answer this question, enter you answer as a formula. In addition to the usual guidelines, two more instructions for this problem only : write as single variable p and as m. and these can be used as inputs of functions as usual variables e.g log(p), m^2, exp(m) etc. Remember p represents the product of s only, but will not work...
1. (50 points) Suppose X1, ..., Xn form a random sample from a N(u,02) distribution with p.d.f. Fe 202, for – V2110 <x< . Assume that o = 2 is known. a) (10 points) Derive the 90% confidence interval for u that has the shortest length. You must show all details including the pivot you use. b) (8 points) Show that the sample mean is an efficient estimator for u. Assume in (c)- (f) that the prior distribution of u...
3. Let X1, X2, . . . , Xn be a random sample from a distribution with the probability density function f(x; θ) (1/02)Te-x/θ. O < _T < OO, 0 < θ < 00 . Find the MLE θ
4. Let X1, X2, ...,Xn be a random sample from a normal distribution with mean 0 and unknown variance o2. (a) Show that U = <!-, X} is a sufficient statistic for o?. [4] (c) Show that the MLE of o2 is Ô = 2-1 X?. [4] (c) Calculate the mean and variance of Ô from (b). Explain why ő is also the MVUE of o2. [6]
Let X1, X2, ..., Xn be a random sample from a Gamma( a , ) distribution. That is, f(x;a,0) = loga xa-le-210, 0 < x <co, a>0,0 > 0. Suppose a is known. a. Obtain a method of moments estimator of 0, 0. b. Obtain the maximum likelihood estimator of 0, 0. c. Is O an unbiased estimator for 0 ? Justify your answer. "Hint": E(X) = p. d. Find Var(ë). "Hint": Var(X) = o/n. e. Find MSE(Ô).
6.1.10. Let X1, X2..... Xn be a random sample from a N(0,0%) distribution, where o? is fixed but-X <O<O. (a) Show that the mle ofis X. (b) If is restricted by 0 < < oc, show that the mie of 8 is 8 = max{0,X}.
5. Let X1, X2,. , Xn be a random sample from a distribution with pdf of f(x) (0+1)x,0< x<1 a. What is the moment estimator for 0 using the method of moments technique? b. What is the MLE for 0?