Let X₁, X2,..., Xn be a random sample on the random variable that is uniformly distributed over the interval (1,0) Cit 1:1
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- Let X be a random variable with the function, -(x -A) "for x > 2, Let f (x) = { elsewhere. Derive u and show that T = X is biased estimator of 2 . Can you modify T =X in order to get an unbiased estimator of 2.Suppose that Y, Y2,.-.,Y, are independent random variables from a gamma distribution of the parameter (2,6+4). a) Use the method of moment to obtain estimator of B. b) Show that the estimator B, obtained in part a) is unbiased. c) Show that the estimator B is a minimum variance unbiased estimator of ß.Let X1, X2,…. Xn be a random sample from Poisson distribution with parameter , obtain Cramer Rao lower bound for the variance of unbiased estimators of lamda
- An ordinary (fair) coin is tossed 3 times. Outcomes are thus triple of “heads” (h) and tails (t) which we write hth, ttt, etc. For each outcome, let R be the random variable counting the number of tails in each outcome. For example, if the outcome is hht, then R (hht)=1. Suppose that the random variable X is defined in terms of R as follows X=6R-2R^2-1. The values of X are given in the table below. A) Calculate the values of the probability distribution function of X, i.e. the function Px. First, fill in the first row with the values X. Then fill in the appropriate probability in the second row.a) Let X₁, X₂, X3,... X, be a random sample of size n from population X. Suppose that X-N (0,1) and Y = -√n. i) Show that the standard score of the sample mean X, is equal to Y. ii) Show that the mean and variance of the random variable Y are 0 and 1, respectiv iii) Show using the moment generating function technique that Y is a standard normal random variable.Q3) Let X1,X2,. X, be a random sample from the truncated exponential distribution with pdf: f(x,0) = Please else (a) Derive the method of moment estimator of 0; (b) Derive the MLE of 0. (c) Are the MOME and the MLE unbiased estimators for 0? (d) Compare the MSE of the MOME and the MLE for 0. Which one is a better estimator for 0
- Let Z be nomrally distributed with mean 0 and variance 1. Let Z1 ,.., Zn be an iid random sample, all distributed as Z. Find the moment-generating function of Z2. please show all your work especially when intergrating. do not skip any minor details.Let X₁, X2, X3, X4 be a random sample of size 4 from a population with the following distribution function f(x; 0) = xº e Г(7)В7' if x > 0 elsewhere Where, ß > 0. a) Find the maximum likelihood estimator of the parameter ß. b) Is the maximum likelihood estimator of the parameter ß unbiased or not? c) Find the variance of the maximum likelihood estimator of the parameter ß. d) What is the fisher information in the sample of size n about the parameter ß. e) What is the Cramer-Rao lower bound for the variance of unbiased estimator of the parameter ß? f) Is this maximum likelihood estimator an efficient estimator of ß?Let ZZ be a discrete random variable taking one of the four distributions covered in Chapter 10. Suppose you know that Var(Z)=(k+1)E(Z)Var(Z)=(k+1)E(Z) where kk is the last non-zero digit of your student ID number. Determine the distribution of ZZ and find its parameter(s), explaining your argument carefully.
- Suppose X1, X2, . ,X, be iid random samples from Uniform(a, b), where b > a. ... Find the method of moments estimators for a and b and find the MLES of a and b.Q11. Let X1,X 2,.,X, be a random sample from a Poisson distribution with parameter 2. (a) Find the Cramer-Rao lower bound for the variance of any unbiased estimator of 1. (b) Find the maximum likelihood estimator (m.l.e.) of å. (c) Is this m.l.e. unbiased and does its variance attain the Cramer-Rao lower bound?Let Y1, . . . , YN be a random sample from the Normal distribution Yi ∼ N(ln β, s2) where s^2is known.Find the maximum likelihood estimator of b from first principles.Find the Score function, the estimating equation and the information matrix using GLM