The normal distribution \mathcal{N}(\theta ,1) with with mean \theta and known variance \sigma ^2=1 has pdf

\displaystyle \displaystyle f_{\theta }(y) \displaystyle = \displaystyle \frac{1}{\sqrt{2\pi }}e^{-\frac{(y-\theta )^2}{2}}.
Rewrite f_{\theta } in the form

\displaystyle \displaystyle f_\theta (y) \displaystyle = \displaystyle h(y) e^{\eta (\theta )T(y)-B(\theta )}\qquad \text {where } \eta (\theta ),\, T(y):\mathbb {R}\to \mathbb {R},
and enter the product \eta (\theta )T(y) below.

\eta (\theta ) T(y)=\quad

1 answer

To rewrite the given pdf in the desired form, we need to express it as the product of two functions: $h(y)$ and $e^{\eta(\theta)T(y)-B(\theta)}$.

In this case, we have:

$h(y) = \frac{1}{\sqrt{2\pi}}$

$\eta(\theta) = -\frac{(y-\theta)^2}{2}$

$T(y) = 1$

$B(\theta) = 0$

Therefore, $\eta(\theta)T(y) = -\frac{(y-\theta)^2}{2}$.