Suppose that {X}}=1 are iid random variables uniformly distributed random variables with density fr A f(x;...
S. 14 points] Suppose random variables X, x.. X, are iid (independent, identical distributed) with density function (with 0>0 and x20) (a) Find the MLE (maximal likelihood estimate) for the parameter 9 (b) Explain (without mathematical proof) how will you check whether your estimate ,f(x) = 3ar'e® in (a) is an unbiased estimate or not?
Problem 4 Define f(x) as follows θ2 -1<=x<0 1-θ2 0<=x>1 0 otherwise Let X1, … Xn be iid random variables with density f for some unknown θ (0,1), Let a be the number of Xi which are negatives and b be the number of Xi which are positive. Total number of samples n = a+b. Find he Maximum likelihood estimator of θ? Is it asymptotically normal in this sample? Find the asymptotic variance Consider the following hypotheses: H0: X is...
Let Xi,..., Xn iid from random variables with probability density function, (0+1)x" 1, ?>0 (x)o for 0 < otherwise (a) Find the method of moments estimator for ? (b) Find the mle for (e): Under which condition is the mle valid?
12. Suppose XIX, iid X, P(θ, l), where P(0,1) is the one-parameter Pareto distribution with density f(x)-0/10+1 for l < x < 00, Assume that θ >2, so that the model θ/(0-1)(8-2)2 (a) obtain the MME θι from the first moment equation and the MIE θ2 (b) Obtain the asymptotic distributions of these two estimators. (c) Show that the ML is asymptotically superior to the MME P(0,1) has finite mean θ/(9 -1 ) and variance
5.4.3 Suppose that X,, X" are iid exponential with mean β(> 0), , y, are iid exponential with mean η(> 0), and that the A's are independent of the Ys. Define ½,-. Then. m, n (i) Show that I , is distributed as /m (ii) Determine the asymptotic distribution of T m, n 2m, 2n as n ->o, when is m, n kept fixed; (ii) Determine the asymptotic distribution of T, as m, when n is kept fixed.
Define f(x) as follows θ2 -1<=x<0 1-θ2 0<=x>1 0 otherwise Let X1, … Xn be iid random variables with density f for some unknown θ (0,1), Let a be the number of Xi which are negatives and b be the number of Xi which are positive. Total number of samples n = a+b. Find he Maximum likelihood estimator of θ? Is it asymptotically normal in this sample? Find the asymptotic variance Consider the following hypotheses: H0: X...
Suppose X and Y are two continuous random variables with probability density functions: fx(x)1 for 1<x2, fx(x) 0 otherwise, and fr (v) 3e3y for y>0, fr (y) 0 otherwise. a) Suppose X and Y are independent, is Z-X+ Y"memoryless"? Justify your answer. b) Suppose that the conditional expected value satisfies E(Y X)-X. Find Cov0), and El(Y-X) expX)]. Suppose X and Y are two continuous random variables with probability density functions: fx(x)1 for 10, fr (y) 0 otherwise. a) Suppose X...
(4) Suppose that {X;}-1 iid random variables from a Binomial distribution Bin(m, p). Using your answer in (3) obtain an approximate 99% confidence interval for the pa- rameter p based on the MLE. Explain how you would estimate the Fisher information matrix.
Let X, Y be iid random variables that are both uniformly distributed over the interval (0,1). Let U = X/Y. Calculate both the CDF and the pdf of U, and draw graphs of both functions.
Question 4 [15 marks] The random variables X1,... , Xn are independent and identically distributed with probability function Px (1 -px)1 1-2 -{ 0,1 fx (x) ; otherwise, 0 while the random variables Yı,...,Yn are independent and identically dis- tributed with probability function = { p¥ (1 - py) y 0,1,2 ; otherwise fy (y) 0 where px and py are between 0 and 1 (a) Show that the MLEs of px and py are Xi, n PY 2n (b)...