Let X_1, X_n be iid Poisson. Let x_bar be an estimator for lambda. Calculate a 95% CI for lambda^3 using the delta method.
Solution:
At 95% C.I. the value of Z is 1.96...
For Lamda^3, the solution is coming soon...
Let X_1, X_n be iid Poisson. Let x_bar be an estimator for lambda. Calculate a 95% CI for lambda^...
Let X1, …, Xn be iid Poisson(λ). Find the maximum likelihood estimator λMLE for λ, when it is given that λ > λ*, where λ* > 0 is a fixed constant. (Note: This is asking you to find the restricted MLE)
2 Method of moments estimator for the uniform distribution Let Y1....,Y, be IID samples from a Uniform(0.02) distribution. Derive method of moments estimators for both ®, and 6
Question 3: Let X1,..., X.be iid Poisson (2) random variables. a. Find the maximum likelihood estimate for X. b. Obtain the Fisher expected information. c. Obtain the observed information evaluated at the maximum likelihood estimate. d. For large n, obtain a 95% confidence interval for based on the Central Limit Theorem. e. Repeat part (a), but use the Wald method. f. Repeat part (d), but use the Score method. 8. Repeat part (a), but use the likelihood ratio method.
Suppose X1,. , Xn are iid Poisson(A) random variables. Show by direct calculation without using any theoremm in mathematical statistics, that (a) Ση! Xi/n is an unbiased estimator for λ. (b) X is optimal in MSE among all unbiased estimators. This is to say, let T be another unbiased estimator, then EA(X) EA(T2
Assume a Poisson distribution. Find the following probabilities. a. Let lambda equals7.0, find P(Xgreater than or equals 3 ). b. Let lambda equals0.6, find P(Xless than or equals 1). c. Let lambda equals6.0, find P(Xless than or equals 2).
Suppose X1 and X2 are iid Poisson(θ) random variables and let T = X1 + 2X2. (a) Find the conditional distribution of (X1,X2) given T = 7. (b) For θ = 1 and θ = 2, respectively, calculate all probabilities in the above conditional distribution and present the two conditional distributions numerically.
Let X1, X2, ..., X, be iid random variables with a "Rayleigh” density having the following pdf: f(x) = 2x2=+*10, 2 > 0 > 0 V лв a) (3 points) Find a sufficient estimator for using the Factorization Theorem. b) (3 points) Find a method of moments estimator for 0. Small help: E(X1) = c) (7 points) What is the MLE of 02 +0 - 10 ? d) (7 points) For a fact, IX has a Gamman, o) distribution. Using...
Let X1, X2, ..., X, be iid random variables with a "Rayleigh" density having the following pdf: f(x) = 6-2°/0, a>0, 0x0 a) (3 points) Find a sufficient estimator for 0 using the Factorization Theorem. b) (3 points) Find a method of moments estimator for 6. Small help: E(X.) = V** c) (7 points) What is the MLE of 02 +0 -10? d) (7 points) For a fact, Li-1 X? has a Gammain,6) distribution. Using this information, find a consistent...
Let {X(t); t >= 0) be a Poisson process having rate parameter lambda = 1. For the random variable, X(t), the number of events occurring in an interval of length t. Determine the following. (a) Pr(X(3.7) = 3|X(2.2) >= 2) (b) Pr(X(3.7) = 1|X(2.2) <2) (c) E(X(5)|X(10) = 7)
For all of following, calculate the A) Posterior Distribution B)Bayes estimator of θ C) Predictive probability 1) yi iid∼ Bern(θ), i = 1, . . . , n1, and yj iid∼ Bern(2θ), j = n1 + 1, . . . , n1 + n2, yi and yj mutually independent . Use θ ∼ Beta(α, β) for prior 2) Same as problem 1 but with Bin(Mi,θ) and Bin(Mi, 2θ) instead of Bern(θ) and Bern(2θ), respectively. Use θ ∼ Beta(α, β) for...