(Created page with "=Proof that <math>I(θ) = E[(s(θ;X))^2]</math>= Recall that: <div style="margin-left: 3em;"> <math> \begin{align} \bar Var(Y) &= E[(Y-E(Y))^2]\\ &= \int_a^b g(x) dx \\ &= \fr...")
 
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\begin{align}
 
\begin{align}
 
\bar Var(Y) &= E[(Y-E(Y))^2]\\
 
\bar Var(Y) &= E[(Y-E(Y))^2]\\
&= \int_a^b g(x) dx \\
+
&= E[Y^2-2YE[Y]+(E[Y])^2]\\
 
&= \frac{\mu_0}{2 \pi a \cdot b}
 
&= \frac{\mu_0}{2 \pi a \cdot b}
 
\end{align}
 
\end{align}
 
</math>
 
</math>
 
</div>
 
</div>

Revision as of 21:55, 6 December 2020

Proof that $ I(θ) = E[(s(θ;X))^2] $

Recall that:

$ \begin{align} \bar Var(Y) &= E[(Y-E(Y))^2]\\ &= E[Y^2-2YE[Y]+(E[Y])^2]\\ &= \frac{\mu_0}{2 \pi a \cdot b} \end{align} $

Alumni Liaison

Ph.D. 2007, working on developing cool imaging technologies for digital cameras, camera phones, and video surveillance cameras.

Buyue Zhang