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change notation in the MLE lecture notes
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zhentaoshi committed Feb 24, 2021
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34 changes: 21 additions & 13 deletions lec_notes_lyx/lecture7.lyx
Expand Up @@ -447,7 +447,15 @@ Asymptotic Normality

\begin_layout Standard
The next step is to derive the asymptotic distribution of the MLE estimator.

Let
\begin_inset Formula $s\left(x;\theta\right)=\partial\log f\left(x;\theta\right)/\partial\theta$
\end_inset

and
\begin_inset Formula $h\left(x;\theta\right)=\frac{\partial^{2}}{\partial\theta\partial\theta'}\log f\left(x;\theta\right)$
\end_inset


\end_layout

\begin_layout Theorem
Expand All @@ -460,7 +468,7 @@ name "thm:mis-MLE"
Under suitable regularity conditions, the MLE estimator
\begin_inset Formula
\[
\sqrt{n}\left(\widehat{\theta}-\theta_{0}\right)\stackrel{d}{\to}N\left(0,\left(E\left[\frac{\partial^{2}\log f\left(x;\theta_{0}\right)}{\partial\theta\partial\theta'}\right]\right)^{-1}\mathrm{var}\left[\frac{\partial\log f\left(x;\theta_{0}\right)}{\partial\theta}\right]\left(E\left[\frac{\partial^{2}\log f\left(x;\theta_{0}\right)}{\partial\theta\partial\theta'}\right]\right)^{-1}\right).
\sqrt{n}\left(\widehat{\theta}-\theta_{0}\right)\stackrel{d}{\to}N\left(0,\left(E\left[h\left(x;\theta_{0}\right)\right]\right)^{-1}\mathrm{var}\left[s\left(x;\theta_{0}\right)\right]\left(E\left[h\left(x;\theta_{0}\right)\right]\right)^{-1}\right).
\]

\end_inset
Expand Down Expand Up @@ -557,7 +565,7 @@ When

.
Notice that
\begin_inset Formula $E\left[\frac{\partial}{\partial\theta}\log f\left(x;\theta_{0}\right)\right]=\frac{\partial}{\partial\theta}Q\left(\theta_{0}\right)=0$
\begin_inset Formula $E\left[s\left(x;\theta_{0}\right)\right]=\frac{\partial}{\partial\theta}Q\left(\theta_{0}\right)=0$
\end_inset

if differentiation and integration are interchangeable.
Expand All @@ -574,7 +582,7 @@ noprefix "false"
follows
\begin_inset Formula
\[
\sqrt{n}\frac{\partial}{\partial\theta}\ell_{n}\left(\theta_{0}\right)\stackrel{d}{\to}N\left(0,\mathrm{var}\left[\frac{\partial}{\partial\theta}\log f\left(x;\theta_{0}\right)\right]\right).
\sqrt{n}\frac{\partial}{\partial\theta}\ell_{n}\left(\theta_{0}\right)\stackrel{d}{\to}N\left(0,\mathrm{var}\left[s\left(x;\theta_{0}\right)\right]\right).
\]

\end_inset
Expand All @@ -590,7 +598,7 @@ noprefix "false"
\end_inset

follows
\begin_inset Formula $\frac{\partial}{\partial\theta\partial\theta'}\ell_{n}\left(\dot{\theta}\right)\stackrel{p}{\to}E\left[\frac{\partial^{2}}{\partial\theta\partial\theta'}\log f\left(x;\theta_{0}\right)\right]$
\begin_inset Formula $\frac{\partial}{\partial\theta\partial\theta'}\ell_{n}\left(\dot{\theta}\right)\stackrel{p}{\to}E\left[h\left(x;\theta_{0}\right)\right]$
\end_inset

(sufficient if we assume
Expand Down Expand Up @@ -641,7 +649,7 @@ true
(Fisher) information matrix
\emph default
, and
\begin_inset Formula $\mathcal{H}\left(\theta_{0}\right):=E_{f\left(x;\theta_{0}\right)}\left[\frac{\partial^{2}}{\partial\theta\partial\theta'}\log f\left(x;\theta_{0}\right)\right]$
\begin_inset Formula $\mathcal{H}\left(\theta_{0}\right):=E_{f\left(x;\theta_{0}\right)}\left[h\left(x;\theta_{0}\right)\right]$
\end_inset

is called the
Expand Down Expand Up @@ -714,15 +722,15 @@ Because
\begin_inset Formula
\begin{align}
0 & =\int\frac{\partial}{\partial\theta}f\left(x;\theta_{0}\right)dx=\int\frac{\partial f\left(x;\theta_{0}\right)/\partial\theta}{f\left(x;\theta_{0}\right)}f\left(x;\theta_{0}\right)dx\nonumber \\
& =\int\left[\frac{\partial}{\partial\theta}\log f\left(x;\theta_{0}\right)\right]f\left(x;\theta_{0}\right)dx=E_{f\left(x;\theta_{0}\right)}\left[\frac{\partial}{\partial\theta}\log f\left(x;\theta_{0}\right)\right]\label{eq:info_eqn_1}
& =\int\left[s\left(x;\theta_{0}\right)\right]f\left(x;\theta_{0}\right)dx=E_{f\left(x;\theta_{0}\right)}\left[s\left(x;\theta_{0}\right)\right]\label{eq:info_eqn_1}
\end{align}

\end_inset

where the third equality holds as by the chain rule
\begin_inset Formula
\begin{equation}
\frac{\partial}{\partial\theta}\log f\left(\theta_{0}\right)=\frac{\partial f\left(x;\theta_{0}\right)/\partial\theta}{f\left(x;\theta_{0}\right)}.\label{eq:ell_d}
s\left(x;\theta_{0}\right)=\frac{\partial f\left(x;\theta_{0}\right)/\partial\theta}{f\left(x;\theta_{0}\right)}.\label{eq:ell_d}
\end{equation}

\end_inset
Expand All @@ -744,10 +752,10 @@ noprefix "false"
, according to the chain rule:
\begin_inset Formula
\begin{align*}
0 & =\int\left[\frac{\partial^{2}}{\partial\theta\partial\theta'}\log f\left(x;\theta_{0}\right)\right]f\left(x;\theta_{0}\right)dx+\int\left[\frac{\partial}{\partial\theta}\log f\left(x;\theta_{0}\right)\right]\frac{\partial}{\partial\theta'}f\left(x;\theta_{0}\right)dx\\
& =\int\left[\frac{\partial^{2}}{\partial\theta\partial\theta'}\log f\left(x;\theta_{0}\right)\right]f\left(x;\theta_{0}\right)dx+\int\frac{\partial}{\partial\theta}\log f\left(x;\theta_{0}\right)\frac{\partial f\left(x;\theta_{0}\right)/\partial\theta}{f\left(x;\theta\right)}f\left(x;\theta_{0}\right)dx\\
& =\int\left[\frac{\partial^{2}}{\partial\theta\partial\theta'}\log f\left(x;\theta_{0}\right)\right]f\left(x;\theta_{0}\right)dx+\int\left[\frac{\partial}{\partial\theta}\log f\left(x;\theta_{0}\right)\frac{\partial}{\partial\theta'}\log f\left(x;\theta_{0}\right)\right]f\left(x;\theta_{0}\right)dx\\
& =E_{f\left(x;\theta_{0}\right)}\left[\frac{\partial^{2}}{\partial\theta\partial\theta'}\log f\left(x;\theta_{0}\right)\right]+E_{f\left(x;\theta_{0}\right)}\left[\frac{\partial}{\partial\theta}\log f\left(x;\theta_{0}\right)\frac{\partial}{\partial\theta'}\log f\left(x;\theta_{0}\right)\right]\\
0 & =\int\left[h\left(x;\theta_{0}\right)\right]f\left(x;\theta_{0}\right)dx+\int\left[s\left(x;\theta_{0}\right)\right]\frac{\partial}{\partial\theta'}f\left(x;\theta_{0}\right)dx\\
& =\int\left[h\left(x;\theta_{0}\right)\right]f\left(x;\theta_{0}\right)dx+\int s\left(x;\theta_{0}\right)\frac{\partial f\left(x;\theta_{0}\right)/\partial\theta}{f\left(x;\theta\right)}f\left(x;\theta_{0}\right)dx\\
& =\int\left[h\left(x;\theta_{0}\right)\right]f\left(x;\theta_{0}\right)dx+\int\left[s\left(x;\theta_{0}\right)s\left(x;\theta_{0}\right)'\right]f\left(x;\theta_{0}\right)dx\\
& =E_{f\left(x;\theta_{0}\right)}\left[h\left(x;\theta_{0}\right)\right]+E_{f\left(x;\theta_{0}\right)}\left[s\left(x;\theta_{0}\right)s\left(x;\theta_{0}\right)'\right]\\
& =\mathcal{H}\left(\theta_{0}\right)+\mathcal{I}\left(\theta_{0}\right).
\end{align*}

Expand Down Expand Up @@ -824,7 +832,7 @@ noprefix "false"
,
\begin_inset Formula
\[
\left(E_{g}\left[\frac{\partial^{2}}{\partial\theta\partial\theta'}\log f\left(x;\theta_{0}\right)\right]\right)^{-1}\mathrm{var}_{g}\left[\frac{\partial}{\partial\theta}\log f\left(x;\theta_{0}\right)\right]\left(E_{g}\left[\frac{\partial^{2}}{\partial\theta\partial\theta'}\log f\left(x;\theta_{0}\right)\right]\right)^{-1},
\left(E_{g}\left[h\left(x;\theta_{0}\right)\right]\right)^{-1}\mathrm{var}_{g}\left[s\left(x;\theta_{0}\right)\right]\left(E_{g}\left[h\left(x;\theta_{0}\right)\right]\right)^{-1},
\]

\end_inset
Expand Down

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