Answer to Question #87369 in Statistics and Probability for Shivam Nishad

Question #87369
Let X1, X2, ...,Xn X , X be a random sample from a distribution with density function
f(x,θ) = {θ^-1 e^-x/θ, if X>0
{0 , otherwise
Show that X=n^-1 ∑Xi is unbiased for θ .
1
Expert's answer
2019-04-04T10:01:35-0400

The first moment of X is 


μ1=E(X)=0xθex/θdx\mu_1=E(X)=\displaystyle\intop_{0}^\infin{x \over \theta}e^{-x / \theta}dx

udv=uvvdu\int udv=uv-\int vdu

u=xθ,du=1θdx,v=θex/θu={x\over\theta}, du={1\over\theta}dx, v=-\theta e^{-x/ \theta}

xθex/θdx=xex/θ+ex/θdx=xex/θθex/θ+C\int {x \over \theta}e^{-x / \theta}dx=-xe^{-x/\theta}+\int e^{-x/\theta}dx=-xe^{-x/\theta}-\theta e^{-x/\theta}+C

μ1=E(X)=0xθex/θdx=[xex/θθex/θ]0=θ\mu_1=E(X)=\displaystyle\intop_{0}^\infin{x \over \theta}e^{-x / \theta}dx=[-xe^{-x/\theta}-\theta e^{-x/\theta}]\begin{matrix} \infin \\ 0 \end{matrix}=\theta

Equating the sample first moment to the population first moment:  


μ1=μ^1\mu_1=\widehat{\mu}_1

θ=1ni=1nXi=Xˉ\theta={1\over n}\displaystyle\sum_{i=1}^nX_i=\bar{X}

Therefore,


θ^=1ni=1nXi=Xˉ\widehat{\theta}={1\over n}\displaystyle\sum_{i=1}^nX_i=\bar{X}

1ni=1nXi=Xˉ{1\over n}\displaystyle\sum_{i=1}^nX_i=\bar{X}  2 is an unbiased estimator of θ\theta.



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