Question

Suppose that X is Poisson, with unknown mean λ, and let X1, ..., Xn be a...

Suppose that X is Poisson, with unknown mean λ, and let X1, ..., Xn be a random sample from X.

a. Find the CRLB for the variance of estimators based on X1, ..., Xn. ̂̅̂

b. Verify that ? = X is an unbiased estimator for λ, and then show that ? is an efficient estimator for λ.

Homework Answers

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Let X1, X2, . . . , Xn be iid exponential random variables with unknown mean...
Let X1, X2, . . . , Xn be iid exponential random variables with unknown mean β. (1) Find the maximum likelihood estimator of β. (2) Determine whether the maximum likelihood estimator is unbiased for β. (3) Find the mean squared error of the maximum likelihood estimator of β. (4) Find the Cramer-Rao lower bound for the variances of unbiased estimators of β. (5) What is the UMVUE (uniformly minimum variance unbiased estimator) of β? What is your reason? (6)...
Let X1, ..., Xn be a sample from an exponential population with parameter λ. (a) Find...
Let X1, ..., Xn be a sample from an exponential population with parameter λ. (a) Find the maximum likelihood estimator for λ. (NOT PI FUNCTION) (b) Is the estimator unbiased? (c) Is the estimator consistent?
Let X1,...,Xn be a random sample from a normal distribution where the variance is known and...
Let X1,...,Xn be a random sample from a normal distribution where the variance is known and the mean is unknown.   Find the minimum variance unbiased estimator of the mean. Justify all your steps.
Let X1, . . . , Xn be iid from a Poisson distribution with unknown λ....
Let X1, . . . , Xn be iid from a Poisson distribution with unknown λ. Following the Bayesian paradigm, suppose we assume the prior distribution for λ is Gamma(α, β). (a) Find the posterior distribution of λ. (b) Is Gamma a conjugate prior? Explain. (c) Use software or tables to provide a 95% credible interval for λ using the 2.5th percentile and 97.5th percentile in the case where xi = 13 and n=10, assuming α = 1 andβ =...
Let X¯ be the sample mean of a random sample X1, . . . , Xn...
Let X¯ be the sample mean of a random sample X1, . . . , Xn from the exponential distribution, Exp(θ), with density function f(x) = (1/θ) exp{−x/θ}, x > 0. Show that X¯ is an unbiased point estimator of θ.
Let X1, . . . , Xn be i.i.d from pmf f(x|λ) where f(x) = (e^(−λ)*(λ^x))/x!,...
Let X1, . . . , Xn be i.i.d from pmf f(x|λ) where f(x) = (e^(−λ)*(λ^x))/x!, λ > 0, x = 0, 1, 2 a) Find MoM (Method of Moments) estimator for λ b) Show that MoM estimator you found in (a) is minimal sufficient for λ c) Now we split the sample into two parts, X1, . . . , Xm and Xm+1, . . . , Xn. Show that ( Sum of Xi from 1 to m, Sum...
Let X1, X2, . . . , Xn be iid following exponential distribution with parameter λ...
Let X1, X2, . . . , Xn be iid following exponential distribution with parameter λ whose pdf is f(x|λ) = λ^(−1) exp(− x/λ), x > 0, λ > 0. (a) With X(1) = min{X1, . . . , Xn}, find an unbiased estimator of λ, denoted it by λ(hat). (b) Use Lehmann-Shceffee to show that ∑ Xi/n is the UMVUE of λ. (c) By the definition of completeness of ∑ Xi or other tool(s), show that E(λ(hat) |  ∑ Xi)...
Let X1, . . . , Xn be a random sample from a Poisson distribution. (a)...
Let X1, . . . , Xn be a random sample from a Poisson distribution. (a) Prove that Pn i=1 Xi is a sufficient statistic for λ. (b) The MLE for λ in a Poisson distribution is X. Use this fact and the result of part (a) to argue that the MLE is also a sufficient statistic for λ.
Suppose X1, . . . , Xn are a random sample from a N(0, σ^2) distribution....
Suppose X1, . . . , Xn are a random sample from a N(0, σ^2) distribution. Find the MLE of σ^2 and show that it is an unbiased efficient estimator.
Let Y1,Y2,Y3,...,Yn denote a random sample from a Poisson probability distribution. (a) Show that sample mean,...
Let Y1,Y2,Y3,...,Yn denote a random sample from a Poisson probability distribution. (a) Show that sample mean, ˆ θ1 = ¯ Y and the sample variance, ˆ θ2 = S2 are both unbiased estimators of θ. (b) Calculate relative efficiency of the two estimators in (a). Based on your calculation, Which of the two estimators in 3a would you select as a better estimator?