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Suppose that X1,…….,Xnform a random sample from the exponential distribution with unknown parameter β. Construct an efficient estimator that is not identically equal to a constant, and determine the expectation and the variance of this estimator.

Short Answer

Expert verified

Mean of the estimator is 1/β and the variance of the estimator is 1/nβ.

Step by step solution

01

Given the information

Suppose that X1,…….,Xnfrom a random sample from an exponential distribution with an unknown parameter β.

02

Finding the expectation and variance of the estimator

The p.d.f of an exponential distribution is,

f (x|β) = βexp(-βx)

As given in exercise 11 of section 8.8, with d(x) = x

Therefore \begin{aligned}T=\sum_{i-1}^{n}X{i}end{aligned}

Know that,

E(Xi) = 1/β and Var (Xi) = 1/β2

Hence,

\begin{aligned}E(T)=E\left(\sum_{i-1}^{n}\right)=\sum_{i-1}^{n}E(X_{i})=\frac{n}{\beta}\end{aligned}

\begin{aligned}Var(T)=Var\left(\sum_{i-1}^{n}X_{i}\right)\end{aligned}

\begin{aligned}Var\left(\sum_{i-1}^{n}X_{i}\right)\end{aligned}

=n/β2

Since any linear function of T will also be an efficient estimator, it follows that x̄n =T/n will be an efficient estimator of 1/β

So,

E(x̄n) = E(T/n)

= n/nβ

= 1/β

Var (x̄n) = Var (T/n)

= 1/n2 Var (T)

= n/n2 β

= 1/nβ

Therefore, the mean of the estimator is 1/β and the variance of the estimator is 1/nβ.

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Most popular questions from this chapter

Suppose that\({{\bf{X}}_{\bf{1}}}{\bf{,}}...{{\bf{X}}_{\bf{n}}}\)form a random sample from a distribution for which the p.d.f. is as follows:

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\(\begin{align}{Y_1} &= 0.8{X_1} + 0.6{X_2},\\{Y_2} &= \sqrt 2 \left( {0.3{X_1} - 0.4{X_2} - 0.5{X_3}} \right),\\{Y_3} &= \sqrt 2 \left( {0.3{X_1} - 0.4{X_2} + 0.5{X_3}} \right)\end{align}\)

Find the joint distribution of \({Y_1},{Y_2},{Y_3}\).

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