## LaTeX Code
Can anyone help me understand this?
Consider the four observations from de Normal Distribution with variance equal to one $y_1 < 10$$, y_2 > 10 $, $5 < y_3 < 10 $ and $ y_4 = 10$.
The likelihood function is?
Would be:
$ \prod_{1}^{4} \frac{1}{\sqrt(2\pi)}\exp{-\frac{(y_i - \theta )^2}{2}}$
Replacing:
$(\int_{-\infty }^{10}\frac{1}{\sqrt(2\pi)}\exp{-\frac{(y_1 - \theta )^2}{2} dy}) \cdot (\int_{10 }^{\infty}\frac{1}{\sqrt(2\pi)}\exp{-\frac{(y_2 - \theta )^2}{2} dy})\cdot (\int_{5}^{10}\frac{1}{\sqrt(2\pi)}\exp{-\frac{(y_3 - \theta )^2}{2}}dy)\cdot (\frac{1}{\sqrt(2\pi)}\exp{-\frac{(10 - \theta )^2}{2}})$
I want to know if this is correct or have another way of solving this problem.
Can anyone help me understand this?
Consider the four observations from de Normal Distribution with variance equal to one $y_1 < 10$$, y_2 > 10 $, $5 < y_3 < 10 $ and $ y_4 = 10$.
The likelihood function is?
Would be:
$ \prod_{1}^{4} \frac{1}{\sqrt(2\pi)}\exp{-\frac{(y_i - \theta )^2}{2}}$
Replacing:
$(\int_{-\infty }^{10}\frac{1}{\sqrt(2\pi)}\exp{-\frac{(y_1 - \theta )^2}{2} dy}) \cdot (\int_{10 }^{\infty}\frac{1}{\sqrt(2\pi)}\exp{-\frac{(y_2 - \theta )^2}{2} dy})\cdot (\int_{5}^{10}\frac{1}{\sqrt(2\pi)}\exp{-\frac{(y_3 - \theta )^2}{2}}dy)\cdot (\frac{1}{\sqrt(2\pi)}\exp{-\frac{(10 - \theta )^2}{2}})$
I want to know if this is correct or have another way of solving this problem.